Survival_Analysis.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "3569fa36",
   "metadata": {},
   "outputs": [],
   "source": [
    "### Survival Analysis in R ###\n",
    "## install packages\n",
    "#install.packages(\"survival\")\n",
    "#install.packages(\"ranger\")\n",
    "#install.packages(\"ggfortify\")\n",
    "#install.packages(\"lubridate\") \n",
    "#install.packages(\"flexsurv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "160e34f7",
   "metadata": {},
   "outputs": [],
   "source": [
    "#R.Version()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "07b58fe7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"dataframe\">\n",
       "<caption>A data.frame: 6 × 8</caption>\n",
       "<thead>\n",
       "\t<tr><th></th><th scope=col>patient</th><th scope=col>treatment</th><th scope=col>time</th><th scope=col>status</th><th scope=col>age</th><th scope=col>sh</th><th scope=col>size</th><th scope=col>index</th></tr>\n",
       "\t<tr><th></th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>1</th><td>1</td><td>1</td><td>65</td><td>0</td><td>67</td><td>13.4</td><td>34</td><td> 8</td></tr>\n",
       "\t<tr><th scope=row>2</th><td>2</td><td>2</td><td>61</td><td>0</td><td>60</td><td>14.6</td><td> 4</td><td>10</td></tr>\n",
       "\t<tr><th scope=row>3</th><td>3</td><td>2</td><td>60</td><td>0</td><td>77</td><td>15.6</td><td> 3</td><td> 8</td></tr>\n",
       "\t<tr><th scope=row>4</th><td>4</td><td>1</td><td>58</td><td>0</td><td>64</td><td>16.2</td><td> 6</td><td> 9</td></tr>\n",
       "\t<tr><th scope=row>5</th><td>5</td><td>2</td><td>51</td><td>0</td><td>65</td><td>14.1</td><td>21</td><td> 9</td></tr>\n",
       "\t<tr><th scope=row>6</th><td>6</td><td>1</td><td>51</td><td>0</td><td>61</td><td>13.5</td><td> 8</td><td> 8</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A data.frame: 6 × 8\n",
       "\\begin{tabular}{r|llllllll}\n",
       "  & patient & treatment & time & status & age & sh & size & index\\\\\n",
       "  & <int> & <int> & <int> & <int> & <int> & <dbl> & <int> & <int>\\\\\n",
       "\\hline\n",
       "\t1 & 1 & 1 & 65 & 0 & 67 & 13.4 & 34 &  8\\\\\n",
       "\t2 & 2 & 2 & 61 & 0 & 60 & 14.6 &  4 & 10\\\\\n",
       "\t3 & 3 & 2 & 60 & 0 & 77 & 15.6 &  3 &  8\\\\\n",
       "\t4 & 4 & 1 & 58 & 0 & 64 & 16.2 &  6 &  9\\\\\n",
       "\t5 & 5 & 2 & 51 & 0 & 65 & 14.1 & 21 &  9\\\\\n",
       "\t6 & 6 & 1 & 51 & 0 & 61 & 13.5 &  8 &  8\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A data.frame: 6 × 8\n",
       "\n",
       "| <!--/--> | patient &lt;int&gt; | treatment &lt;int&gt; | time &lt;int&gt; | status &lt;int&gt; | age &lt;int&gt; | sh &lt;dbl&gt; | size &lt;int&gt; | index &lt;int&gt; |\n",
       "|---|---|---|---|---|---|---|---|---|\n",
       "| 1 | 1 | 1 | 65 | 0 | 67 | 13.4 | 34 |  8 |\n",
       "| 2 | 2 | 2 | 61 | 0 | 60 | 14.6 |  4 | 10 |\n",
       "| 3 | 3 | 2 | 60 | 0 | 77 | 15.6 |  3 |  8 |\n",
       "| 4 | 4 | 1 | 58 | 0 | 64 | 16.2 |  6 |  9 |\n",
       "| 5 | 5 | 2 | 51 | 0 | 65 | 14.1 | 21 |  9 |\n",
       "| 6 | 6 | 1 | 51 | 0 | 61 | 13.5 |  8 |  8 |\n",
       "\n"
      ],
      "text/plain": [
       "  patient treatment time status age sh   size index\n",
       "1 1       1         65   0      67  13.4 34    8   \n",
       "2 2       2         61   0      60  14.6  4   10   \n",
       "3 3       2         60   0      77  15.6  3    8   \n",
       "4 4       1         58   0      64  16.2  6    9   \n",
       "5 5       2         51   0      65  14.1 21    9   \n",
       "6 6       1         51   0      61  13.5  8    8   "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "### Survival Analysis in R ###\n",
    "## Import prostate_cancer as prost\n",
    "prost <- read.csv(\"prostate_cancer.txt\", header=FALSE, sep =\" \")\n",
    "\n",
    "# Providing column names\n",
    "colnames(prost) = c(\"patient\", \"treatment\", \"time\", \"status\", \"age\", \"sh\", \"size\", \"index\")\n",
    "head(prost)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "954e9b1d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       " [1] 65+ 61+ 60+ 58+ 51+ 51+ 14  43+ 16+ 52+ 59  55+ 68+ 51   2+ 67+ 66+ 66  28+\n",
       "[20] 50  69  67  65+ 24+ 45+ 64+ 61+ 26  42  57+ 70+  5+ 54+ 36  70  67+ 23+ 52 \n",
       "[39] 65+ 24  45+ 64+ 61  21  22  37+ 51  12+ 67+ 61+ 66  65+ 50  35  67  65+ 33+\n",
       "[58] 45+ 62+ 61+ 36  42  57+"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "### The fundamental Surv function\n",
    "library(survival)\n",
    "Surv(prost$time, prost$status)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "febcc65a",
   "metadata": {},
   "outputs": [
    {
     "data": {
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Xg8sqeIdmf60dnZKXs09MHj8cybN48HO4WWmYKd1WoVQrhcrgH20bZqewIAokRM\nTExHR8e4fkyZMuXTTz+VPSN6oscuHMz0GbuioiK73W632ysrK202W+8dXC6X3W7X9oz4dACi\nWlVVVVNTE3Unsjz44IPjx4/vc1N9ff3bb7/9ySefjBw5MsJTAZFnpmBns9mcTqfD4dDSmwg4\nMxdYgOJ0OvuMfQAQPvTYybVw4cKFCxf2uWnNmjVvv/12hOcBZDFTsBNCFBYW5ubmVlRUbNu2\nze12B+Y5q9Wal5dHRzEAKeixA4aKHrtwMNNn7DQpKSmFhYV1dXX+f1ZXV1dYWEiqAyBLR0dH\nWlra//7v/wohPB7PtGnT9M94GWf94YcflvgjAgLRYxcOJjtjBwDGdNddd50/fz45OTk+Pl4I\nkZSUlJaW1tHRoW01yPqbb7752muvPfXUUxH4gRhHd3e3EKKrq0v2IOiJHrtwINgBQAjccccd\nd9xxh/7t7NmzKyoqeu8mdz0tLW2Av4Kqjh07JoTYvXv39OnTZc8ChJ35LsUCAIIzZcqUKVOm\nyJ4i0rTzl9SdGBA9duHAGTsAiBavvvoqH1SHceg9dlOnTpU9izo4YwcA0SIxMTEhIUH2FMA/\nuf/++++77z7t9a5du6xW6/XXX3/99dcvXrz473//u9zZzIgzdgAQLbSKKJ7NA4OYO3fuNddc\n09nZefjw4a6urtjY2BMnTnz00Ud+v7+9vX3//v1vvPHGzJkzZY9pMgQ7AIgWDzzwgBDirbfe\nkj1IuPh8vurq6tbW1sDFU6dOCSEaGhrKy8v1xeTk5MWLF8fGxkZ6RATIzMw8ePBg4Mrdd999\n9913CyEuXrxYUlKybNkySaOZGMEOAKJFZ2en7BHCq76+fsmSJX1ueu6555577rnAldra2uzs\n7IjMhSEbPnz4I488InsKUyLYAQAUkZWVVVNT097eHrj4ox/9aM+ePd/73vduvfVWfTEhISEr\nKyviA2IIOjs7hw0bJnsK8yHYAQAUERcXt2jRoh6LzzzzjBDi2muvzcnJkTEUgnH48OG5c+f+\n8Y9/DOE/tebmZovFMmvWrFAd0Ji4KxYAokV09tjBjN5///2LFy+G9q7Y/Pz8/Pz8EB7QmDhj\nBwDRgh47RLOLFy/KHiESCHYAEC0SExNljwAgvLgUCwDRwu12a1V2USU+Pl4IMXLkSNmDYAi0\nJhr6aILAGTsAiBbK99j1adq0aUKI3jdVwMgyMzOfeOKJwBuZP7/k5ORo+BzROZIAACAASURB\nVCgCwQ4AooXyPXZ9iomJEZz7MZtw9Ni98soroT2gMRHsAACA4YS8x278+PEhPJph8Rk7AABg\nLIcPHx4zZkxVVVUIj9nc3HzgwIEQHtCYOGMHANEimkvsnnrqqdGjR/dY7O7u9vl8Tz75ZEJC\ngpSp0B+9xy6EBcX5+fkWi2Xv3r2hOqAxEewAIFpEZ4+ddgHu5z//eX87TJky5aGHHorgRJCD\nHjsAgFKis8duzZo1eXl5fr+/96ZHH330pZdeam1tjfxUQJgQ7AAgWmgldlarVfYgERUTEzN9\n+vQ+NyUlJUV4GAwSPXZBI9gBQLSIzh47mBE9dkEj2AFAtIjOHjuYET12QSPYAQCigs/nq66u\nDvxE3ZEjR4QQzc3N5eXl+mJycvLixYsHuAjo8/kaGhoyMjJ67zPApsvOFvJjmh09dsEh2AFA\nNNq9e/eWLVv0Wwrsdvt//Md/KLA+gPr6+iVLlvRe3759+/bt2wNXamtrs7Oz+ztOVVWVzWZz\nuVxLly4d/KaBheOYpnb48OG5c+f+8Y9/HGrdya9+9av9+/ffd9998+fPF0L87Gc/e/vtt7VN\nsbGx+rrCCHYAEC1mzJhx/vx57fVvfvOb3/zmN/omr9erBSOzrw8gKyurpqamvb1dXykpKams\nrLzrrrvy8/P1xYSEhKysrAGO09bWpn8d/KaBheOYphZ0j913v/vdixcvTpkyZf78+X6/f8OG\nDUePHtW3aushntVgCHYAEC3+8Ic/6Ke4fvWrX/30pz/VN+n3h5p9fQBxcXGLFi0KXNm2bZsQ\nYvr06SFswYVcXV1dubm5jz76qBDCYrEcOnTo008/1TZZLJbk5GSp00UCwQ4AokXgh7QsFsvY\nsWN772PS9aqqqqamJofD0XtPRJvAT+bFx8fHx8dLHCbyeFYsAMD0Nm3a9PDDD8ueAiETdI/d\n1KlTp06dGoaJTIMzdgAA0/P7/X0+W2IwLl26dObMmf62+ny+3bt3nzt3Tl/Zt2+fEOKNN95o\na2trbm7WH1Q1YsQI7arfG2+8oV/+04wZM2bRokVaTOl9QP2Y1dXVHo8n8ICzZs3av39/72Pq\nBxwxYoSSD7oNusfuwIEDob2X1nQIdgCAKDVixAghRHFxcXFx8VDfu2nTpiA2DewXv/jFUI85\nevToxsbG/h6tYV5B99hF24XX3gh2AIAoVVhYePLkybFjxw7wQILu7u6PPvqoq6tLXzl9+nRD\nQ8P8+fMnTpx45syZ7u5ubT0mJubSpUtvvfXW/PnzJ02aFHiQ2NjYq666SvtTeh9QP+a8efMS\nExMDDzh27NgPPvhA++MCj6kd8ODBg7t37z5y5Ih6wU4E22O3devWa6+9VvlbXwdAsAMAmF56\nevqpU6eG+q7p06cHVhMPUnl5eV5e3sMPP7xixYrBbxrMMf/rv/5rSMcsLS3dvXv3UOc3haB7\n7L797W/b7fYg/rEqg5snAACmt3btWo/HI3sKhIzeYzfUN/p8Pp/PF46RzIJgBwAAoAiCHQDA\n9KqqqpxOp+wpAPkIdgAA06PHTjH02AWNmycAAKb3eXrshkp7fFmfDzEbYFPkj2lq9NgFjWAH\nAMAQ5OTkeDyejIyMIW2K8DF9Pl9DQ0NGRkYQJ72MgB67oHEpFgCAIYiLi1uwYEGfgWmATRE+\nZlVVVWZm5uuvvz7USYyjs7MziHdt3bq1oaEh5MOYCMEOAGB66enpc+fOlT2FgbS1telfzejw\n4cNjxoypqqoa6hu//e1vP/nkk+EYySwIdgAA06PHTjH02AWNYAcAAKAIgh0AwPTosQM03BUL\nADC9TZs2VVZWOhwO2YMgNAJ77Orq6mpra7V1i8WyZMmS9PT0/tbpsSPYAQBML5I9dkZz//33\njxo1qq2traurS1/89NNPhRDf/e53A3ubY2Njk5KSLBZLQkLChg0bvvzlL0sYd3ACe+zWrFmz\nZ88efdO+ffvKy8v7W6fHjmAHAIApzZ0795prruns7Pzggw9OnTrVe4cPP/ywx8rkyZPj4uKO\nHz++fft2Iwe7wB6711577b333tM3XXPNNQOs02NHsAMAwJQyMzMPHjwohPD5fHv27Glvb9c3\n1dTUrFu37rHHHrvhhhv0xYSEBKvVumXLlvz8/KNHj0Z+4OCMGzdu3Lhxg1+PcgQ7AIDppaen\n93nKKkrExcUtWrQocOXMmTNCiOuuuy4nJ6fHztpV2o6OjoiNh0jirlgAgOnRYwdoCHYAAACK\nINgBAEyPHjtAw2fsAACmt2nTpoqKikWLFo0cOfLaa6/VFk+dOnX69GkhxL/8y79MmDBB6oCR\nlpSUpH9FVCHYAQBMLzY2tqOj4/rrrxdCvPjii1/96lc/+uijq6++urOzUwgxcuTI06dPR1XK\nycnJ8Xg8GRkZPp+vurq6tbVV39TQ0CCEOHXqlNYGp0tOTl68eLHWCQzzItgBAEzv0Ucf1VJd\nbGzsjTfeKIQYP3680+lsa2urrKysqak5c+ZMVAW7uLi4BQsWCCFqa2uXLFnSe4f9+/fn5eX1\nWHzzzTcTExMzMjKGGu98Pl9DQ0OfbxxgE8KBYAcAML25c+fOnTs3cCUmJub+++8XQsyZMycm\nJmbSpEmSRpMsKyurpqYmsOJux44dzzzzzJe//OXHH388cM+EhIS2trYbb7zR5XItXbp0SH9K\nVVWVzWbr840DbEI4EOwAACpbtmzZsmXLZE8hTe+Ku5aWFiHE+PHje1fcaRdn29rahvqnaG/p\n840DbEI4cFcsAACAIgh2AACV7dq16+tf/3pXV5fsQYBIINgBAFRWWVm5devWkydPyh4EiAQ+\nYwcAQBQZOXKkECI+Pr53E8qePXv0r4ECm1B6v0t/S11d3d/+9rcLFy7of1BaWpr2qLcex6Ra\nJXwIdgAARJGFCxcKISoqKsaNG9fnPQ0lJSUlJSU9FpOSkuLi4oQQPp+vvzshNm7c2N8f2vuY\n2gEnTpxYXV09ceLEof4t0B+CHQAAUeQLX/jCV7/61Y8//tjv97e2tnZ3d+ubzpw58957702f\nPn3s2LGBb4mJiRkzZozFYhFC9H6X/sarr746Pj7e7/drixaLZeTIkWfPnu19TO2Ap06dOnDg\nwLvvvkuwCyGCHQBAZTfeeONf//rXqO2x6y0uLu7FF1/sc1N5eXleXt7TTz+9YsWKIR1Te+NP\nfvKT3m8c4JilpaWrVq0a0h+Ey+LmCQCAypYtW7Zr165hw4bJHgSIBIIdAACAIgh2AACV0WOH\nqEKwAwCojB47RBWCHQAAEEKIpKQk/Wuo3hj0MREc7ooFAABCCJGTk+PxeDIyMkL4xqCPieAQ\n7AAAgBBCxMXFLViwILRvDPqYCA7BDgCgMnrsEFX4jB0AQGX02CGqEOwAAAAUQbADAKiMHjtE\nFYIdAEBl9NghqhDsAAAAFEGwAwAAUATBDgAAQBH02AEAVEaPHaIKZ+wAACrTeuzcbvecOXNm\nfmbhwoXnz5+XPRoQegQ7AID6EhMTk5KSxn5m1KhRsbGxHo9n3rx5J06ckD0dEDJcigUAqC8z\nM7O+vr7HYmNjY2Nj46FDh6ZOnSplKiDkOGMHAACgCIIdAACAIkwZ7Fwul/7a6/WuXLkyOzs7\nOzt748aNXq9X4mAAABOxWCz6V0ANJgt2GzdutFgsdrtd/zY1NbWsrMztdrvdbofDkZqaunHj\nRrlDAgBM4eabb77zzjszMjJkDxKluru79a8IFTMFO5fL5XA4hBAFBQWB3zqdzpaWlpaWFqfT\nKYRwOByBp/QAAOjTzJkzt27dOmbMGNmDRKkDBw4IIfbv3y97EKWY6a7Y9evXCyEqKyttNlvv\nb4UQhYWFQgiHw7F+/Xp9EQAAGNClS5eEEBcuXJA9iFLMdMbO7XYLIfTE1uNbjZbttE0AAAyA\nHjuox0zBDgCAENJ77GQPAoSMmYKd1WoVAbfE6p+0C9xH+1bbEwAAIKqY6TN2RUVFdrvdbre3\ntLSkpKSsWbOmrKxs/fr1qampKSkpQgiv16vdMJuXlyd7WAAA8H98Pl91dXVra6u+cuTIESFE\nc3NzeXm5vpicnLx48eLY2FgJIyrBTMHOZrM5nU6t08RqtaalpVmtVrfbrX0rPvtoXUFBgfZJ\nOwAABkCPXSTV19cvWbKk9/r27du3b98euFJbW5udnR2puVRjpmAnhCgsLPziF7+4fv16rbhO\nX9dfO51OUh0AYDD0Hrvq6upt27b5/X5t/cYbb/za174mhDDLuilkZWXV1NS0t7frKyUlJZWV\nlXfddVd+fr6+mJCQkJWVJWNAVfhxOffee68QYt26dbIHAQCExcqVKwP/zbhw4UJzrZvUt7/9\nbSHEY489JnuQIautrRVCOJ1O2YP0weL/LPijP9/4xjeef/75devWFRUVyZ4FABB6fr//7Nmz\n+rdJSUlxcXEmWjepgoKCX/7yl4899tjjjz8ue5ahqaurW7hwoTEvEpr4FyIken+Ws7ejR48K\nnnkCAOqyWCxjx4413brH41m1atWOHTumTp3ae2dEJwWDnfYx2EGeiezvs5y90WAJADAUvYeP\nYAedgsFuSHp/lrO3DRs27Ny5k//ZAAAAg1Mw2A3pU4NxcXGLFi0aeJ8tW7YIIWJizFTmDACA\nwSUmJgohRowYIXsQpRBWAAAwJbP38M2aNUsIkZGRIXsQpRDsAAAwJb2HT/YgQdIuhXFBLLRM\neSnW6/VWVFQ0Nzc3NTVpK2lpabNnz87NzdWeLQYAgPJmzpy5detW2VPAWEwW7Lxeb35+fuAz\nJzTaisPhsFqtmzdvJt4BAIAoZKbzn16vNzU11e12W63WysrKln9WWVmpPzrW6/XKHhYAgPDy\neDzz5s2jjQuBzBTsiouLhRAFBQV1dXU2my3ln9lstrq6uoKCAn1PAAAUpvfYyR4EBmKmYFdW\nViaEKC0tHWAfbau2JwAAQFQxU7ADAADAAMwU7KxWqxDC5XINsI+2VdsTAACFmb3HDuFgpmBX\nVFQkhLDb7f1lO5fLZbfb9T0BAFCY2XvsEA5mqjux2WxOp9PhcGjpTQScmQssQHE6nTabTcJ8\nAABEED126M1MwU4IUVhYmJubW1FRsW3bNrfbHZjnrFZrXl4eHcUAgOhRXV1dVlbW3d2tffvv\n//7v991332XXhw0b9sgjj2hP9IJiTBbshBApKSmFhYWFhYWyBwEAQLIdO3b87ne/0789ceKE\nFuAuuz558uSnn3464vMi7Mz0GTsAABCopKTEH0C/kDXA+rFjx4QQ+sk8KIZgBwBAFImPjxdC\nJCQkyB4EYWG+S7EAACBoEydOfPnll7OysmQPgrAg2AEAEF2WL18uewSEC5diAQCILidPnuzq\n6pI9BcKCYAcAQBQ5e/bsjBkzNmzYIHsQhAXBDgCAKHLu3LmOjo6PP/5Y9iAIC4IdAACAIgh2\nAAAAiiDYAQAQReixUxt1JwAARBGj9di99NJLf/3rX3uvjx49Oj8/f8SIEZEfydQIdgAARBeD\n9NhdeeWVQojnnnuuvx1GjBiRn58fwYlUQLADACC6nDx5cuLEibGxsXLHuP32299555329vbe\nm/bt2/ed73zn0qVLkZ/K7Ah2AABEEa3H7vHHH//P//xP2bOItLS0PtfPnj0b4UmUwc0TAABE\nEXrs1EawAwAAUASXYgEAiF4tLS3Hjh3TXg8bNiwzMzMxMTFi61dcccW8efMi9peNBgQ7AACi\nSGJiosViGTZsmBCis7MzPT394sWL+tYnnnjikUceieT6/v3758+fH9a/clQh2AEAEEUmTJjw\n2muvZWRkCCGGDRv28ssvHz9+XNsUExNz6623Rmz9t7/97ZYtW86cOROpv3pUINgBABBd7Ha7\n/nrp0qV97hOB9ePHj2/ZssVisQw0K4aImycAAIAEN99885133qmdO0SocMYOAABIMHPmzK1b\nt8qeQjWcsQMAAFAEwQ4AAEjg8XjmzZt34sQJ2YMohWAHAAAkaGxsbGxsPHTokOxBlEKwAwAA\nUATBDgAAQBEEOwAAIIHWYEePXWgR7AAAgAT02IUDPXYAAEACeuzCgTN2AAAAiiDYAQAACeix\nCweCHQAAkIAeu3Ag2AEAACiCYAcAAKAIgh0AAJCAHrtwINgBAAAJ6LELB3rsAACABPTYhQNn\n7AAAABRBsAMAABIM0GPX1dUlhOju7o74UKZHsAMAABIM0GPX0NAghDhw4EDEhzI9gh0AADCW\nCxcuCCEuXbokexDzIdgBAAAogmAHAAAkoMcuHAh2AABAAnrswoEeOwAAIIHeY+fz+aqrq1tb\nW/VNzc3NQogjR46Ul5fri8nJyYsXL46NjY38qCZCsAMAADLV19cvWbKk9/pf/vKXv/zlL4Er\ntbW12dnZkZrLlAh2AABAAo/Hs2rVqh07dmRlZdXU1LS3t+ubNm/e/Nvf/tZutz/44IP6YkJC\nQlZWloxJzYRgBwAAJNB77KZOnbpo0aLATTU1NUKIKVOm5OTkSJrOrLh5AgAAQBEEOwAAAEUQ\n7AAAgAT02IUDwQ4AAEhAj104cPMEAACQQO+x623EiBFCiMTExMhOpALO2AEAAGOZP3++EGLW\nrFmyBzEfgh0AAJDA4/HMmzfvxIkTvTdpj5eIiSGlDBk/MgAAIIHeYyd7EKUQ7AAAABRBsAMA\nAFAEwQ4AAEhAj104EOwAAIAE9NiFAz12AABAggF67BA0ztgBAAAogmAHAAAkGKDHDkEj2AEA\nAAnosQsHgh0AAIAiCHYAAACKINgBAAAJ6LELB4IdAACQgB67cKDHDgAASECPXThwxg4AAEAR\nBDsAACABPXbhQLADAAAS0GMXDgQ7AAAARRDsAACAafh8vr1793Z1dckexKAIdgAAQILgeuyq\nqqoyMzNff/318AxlegQ7AAAgQXA9dm1tbfpX9EaPHQAAkIAeu3DgjB0AAIAiCHYAAEACeuzC\ngUuxAABAAr3HburUqf3t4/P5qqurW1tb9ZU9e/boXwMlJycvXrw4NjY2TNOaBcEOAAAYi3ar\n7Pe///01a9b0eZ9ESUlJSUlJj8WkpKT4+PhHH330wQcfjMSUhkSwAwAAxjJ//vzbb7/93Llz\nfr+/tbW1u7tb33TmzJn33ntv+vTpY8eODXxLTEzMmDFjdu3aVVNTQ7ADAACIqAF67JKTk7dv\n397nu8rLy/Py8p5++ukVK1b03pqQkBDaIU2HmycAAIAEwfXYYWCKnLHLzs4WQtTV1ckeBAAA\nDAo9duGgSLBzu92yRwAAAJDMTMFOOy03yB04ewcAgJF5PJ5Vq1bt2LFjgLoTDJWZgp243Jk5\nztsBAGAWg+mx6y0pKUn/it7MdPNEXV2d1WoVQjidTv8/03bovQIAAFSSk5Pj8XhuueUW2YMY\nlJmCnRCirq7O6XQ6HI7LXpYFAADqiYuLW7BgAU+Y6I/Jgp0QorCwsKWlxe12WywWr9crexwA\nABCMAXrsEDTzBTshREpKit/vt1qtqampGzdulD0OAAAYMnrswsGUwU5TV1dXUFDAZVkAAMxI\n67EbM2aM7EGUYuJgJ4QoLS2trKzkZlgAAABh9mAnhLDZbNwJCwCA6Xg8nnnz5p04cUL2IEox\nfbADAABmpPfYyR5EKQQ7AAAARZjsyRODod04Pcgrsz6fr7q6urW1dYB9jh49KoTo7u4OxXQA\nAOD/vPLKKzfffLMQYteuXT/5yU98Pp+2np2dvXbtWpmTmZOCwW5I6uvrlyxZMpg9+RAAAAAh\nNGvWrAkTJuzbt0/7tqGhwePx6Fvb2toIdkFQMNgN6S6KrKysmpqa9vb2AfbZsGHDzp07eUQx\nAAAhdMMNN3z44Yf6tw899NBDDz0kcR41KBjshiQuLm7RokUD77NlyxYhREwMn0cEACBCOjs7\nhw0bJnsK8yGsAAAAYzl8+PCYMWOqqqpkD2I+pjxj5/V6Kyoqmpubm5qatJW0tLTZs2fn5uam\npKTInQ0AAHxO77///sWLF//+97/n5OTInsVkTBbsvF5vfn5+70dNaCsOh8NqtW7evJl4BwAA\nopCZgp3X601NTRVCWK3WoqIi7bWupaVl/fr1brc7NTW1paWFbAcAAKKNmYJdcXGxEKKgoKC0\ntLT31pSUFJvNtnLlyrKysuLi4j73AQAAxhcbG6t/xZCY6eaJsrIyIcTAiU3bqu0JAADMKDMz\n84knnrj11ltlD2I+ZjpjBwAAosHw4cMfeeQR2VOYkpnO2FmtViGEy+UaYB9tq7YnAAAwqc7O\nTtkjmJKZgl1RUZEQwm6395ftXC6X3W7X9wQAAGZEj13QzBTsbDab0+kUQtjtdovFYrFYsj+j\nfaulOqfTabPZZA8LAACCpPfYyR7EfEz2GbvCwsLc3NyKiopt27a53e7AQjur1ZqXl0dHMQAA\niFomC3ZCiJSUlMLCwsLCQtmDAAAAGIuZLsUCAIBoQI9d0Ah2AADAWOixC5r5LsUCAAC10WMX\nNM7YAQAAw6HHLjgEOwAAYCz02AWNYAcAAIyFHrugEewAAAAUQbADAABQBMEOAAAYCz12QSPY\nAQAAY6HHLmj02AEAAGOhxy5onLEDAACGQ49dcAh2AADAWOixCxrBDgAAGAs9dkEj2AEAACiC\nYAcAAKAIgh0AADAWeuyCRrADAADGQo9d0OixAwAAxkKPXdA4YwcAAAyHHrvgEOwAAICx0GMX\nNIIdAAAwFnrsgkawAwAAUATBDgAAQBEEOwAAYCz02AWNYAcAAIyFHrug0WMHAACMhR67oHHG\nDgAAGA49dsEh2AEAAGOhxy5oBDsAAGAs9NgFjWAHAACgCIIdAACAIgh2AADAWOixCxrBDgAA\nGAs9dkGjxw4AABgLPXZB44wdAAAwHHrsgkOwAwAAxkKPXdAIdgAAwFjosQsawQ4AAEARBDsA\nAABFEOwAAICx0GMXNIIdAAAwFnrsgkaPHQAAMBZ67ILGGTsAAGA49NgFh2AHAACMhR67oBHs\nAACAsdBjFzSCHQAAgCIIdgAAAIog2AEAAGOhxy5o1J0AAABj+Tw9dnV1dbfcckufm+6+++57\n7rnn841mdAQ7AABgLEH32GVmZjY1Ne3fv7/3pnPnzn3wwQcEOwAAgEjr7OwcNmzYUN9VU1PT\n36a0tDS/3//5hjIBPmMHAACMhR67oBHsAACAsdBjFzSCHQAAgCIIdgAAAIog2AEAAGOhxy5o\nBDsAAGAsn6fHLspRdwIAAIwl6B47cMYOAAAYTmdnp+wRTIkzdgAAwFgOHz48d+7cVatWXXXV\nVRaL5Stf+cq1114rhNi7d++uXbu0ffpcj4mJWbFixdVXXy1vdskIdgAAwFguXbp08eLFkpIS\n7duGhoaXXnpJCPG9733P4/Hou/W53tDQ8OKLL0Z8ZKMg2AEAAGP50pe+dPjw4XPnzmnfXnPN\nNdqLysrK9957T9+t9/qSJUvi4+MjO6yxEOwAAIDhpKam9l4cN27cuHHjBlj3eDzjx48P+3AG\nRrADAACKmDlzpuwRJOOuWAAAoIjGxsYPP/xQ9hQyEewAAIAicnJy1qxZI3sKmQh2AABAEW1t\nbW1tbbKnkIlgBwAAoAiCHQAAgCIIdgAAQBGjR48ePXq07Clkou4EAAAoor6+nh47AAAAFdBj\nx6VYAACgCHrsCHYAAEAR9NgR7AAAgCLosSPYAQAAKIJgBwAAoAiCHQAAUAQ9dtSdAAAARdBj\nR7ADAACKoMeOS7EAAEAR9NgR7AAAgCLosSPYAQAARQzQY+f3+y9evNjV1RXhkSKMYAcAANT3\n6aefHjly5PXXX5c9SHgR7AAAgPq6u7uFEMo/l8KUwc7lcrlcrv62rly5cuXKlZGcBwAAGAE9\ndiarO3G5XHa7Xf/WarVu3rw5JSUlcJ+ysjIhRGlpaaSHAwAAUtFjZ6Zgp6c6q9WalpbW1NTk\ndrtTU1NbWlp6ZDsAABCF6LEz06XYV155RQjhdDrr6upKS0vr6uoqKyuFEKmpqV6vV/Z0AABA\nMnrszHTGTrvGmpubq6/YbLbKykq73Z6amur3++WNBgAA5MvJybHb7b/+9a+rq6tbW1sDN124\ncEEIsWfPnsDF5OTkxYsXx8bGRnTKcDJTsNP0uOpqs9mcTqfD4cjOzq6rq5M1FQAAkE7rsauv\nr1+yZEmfO5SUlJSUlASu1NbWZmdnR2S6SDBTsLNarW632+v19sh2hYWFzc3NZWVlGzduLCws\nlDUeAAAwgqysrJqamvb29sDFr33ta//4xz8ee+yxG264QV9MSEjIysqK+IBhZKZgl5aW5na7\nKyoqeqe30tLSpqYmh8MhZTAAAGAccXFxixYt6rGYmJgohLjuuutycnJkDBUhZrp5Qnv6m8Ph\nsFgsvbfW1dVZrVayHQAAUYseOzMFu5SUlJaWFqvV2t8OdXV1BQUFkRwJAAAYR319/TPPPCN7\nCpnMFOyEECkpKXV1dQPcAFtaWur3+7lDFgCAKDRz5swxY8bInkImkwU7AACA/gzQYxcTEyOE\nSEpKiuxEkUawAwAAisjJydE+kd/byJEjZ8yYccstt0R4pAgz012xg6TdWjHIq7E+n693h2EP\nR48eFUJ0d3eHYjoAABAuWo9dn5ssFsvw4cNV6iLuk4LBbkgG6DDs4cSJE+EeBgAA4PNQMNgN\n6c6JPjsMe9iwYcPOnTunTp36uUcDAAAIIwWD3ZD02WHYw5YtW8RnH7oEAACGRY9dtAc7AACg\njPr6+vHjx8ueQiZTBjuv11tRUdHc3NzU1KStpKWlzZ49Ozc3t8djZAEAQPSYOXOm7BEkM1mw\n83q9+fn5bre7x7q24nA4rFbr5s2biXcAAEShxsbGSZMmXXXVVbIHkcZMwc7r9aampgohrFZr\nUVGR9lrX0tKyfv16t9udmpra0tJCtgMAINrk5OTY7fYXXnhB9iDSmCnYFRcXCyEKCgpKS0t7\nb01JSbHZbCtXriwrKysuLu5zHwAAoLABeuyihJnu9CwrKxNCDJzYGMK+XQAADrNJREFUtK3a\nngAAAFHFTMEOAAAAAzBTsLNarUIIl8s1wD7aVm1PAAAQVeixM1OwKyoqEkLY7fb+sp3L5bLb\n7fqeAAAgqtTX1z/zzDOyp5DJTDdP2Gw2p9PpcDi09CYCzswFFqA4nU6bzSZhPgAAIBU9dmYK\ndkKIwsLC3NzcioqKbdu2ud3uwDxntVrz8vLoKAYAIGrRY2eyYCeESElJKSwsLCwslD0IAAAw\nFnrszPQZOwAAgAHQY0ewAwAAUATBDgAAQBEEOwAAoAh67Mx38wQAAECf6uvrx48fL3sKmQh2\nAABAEfTYcSkWAAAoorGx8cMPP5Q9hUwEOwAAoIicnJw1a9bInkImgh0AAFAEPXYEOwAAAEUQ\n7AAAABRBsAMAAIqgx466EwAAoAh67Ah2AABAEfTYcSkWAAAogh47gh0AAFAEPXYEOwAAoAh6\n7PiMHQAAUF9ycrLFYpE9RdgR7AAAgPpeeeUV2SNEAsEOAAAoYoAeuyipQSHYAQAARdBjR7AD\nAACKoMeOu2IBAIAi6LEj2AEAAEXQY0ewAwAAiqDHjmAHAACgCIIdAACAIgh2AABAEQP02EUJ\n6k4AAIAi6LEj2AEAAEXQY8elWAAAoAh67Ah2AABAEfTYEewAAIAi6LEj2AEAACiCYAcAABRh\nsViqqqreeecdIcTbb7+dnJxs+czYsWO1dbVxVywAAFDEU089deTIkUmTJgkhJk+efM8997S3\nt2ubEhIStHW1EewAAIAiHA6H/nr8+PHPPPOMxGGk4FIsAABQn9vtdrvdsqcIO87YAQAA9T3w\nwANCiLfeekv2IOFFsAMAAOrr7OyUPUIkcCkWAABAEQQ7AAAARXApFgAAqG/KlCmyR4gEgh0A\nAFDfq6++arFYZE8RdgQ7AACgvsTERNkjRAKfsQMAAOqjxw4AAEAR9NgBAAAogh47AAAAmAnB\nDgAAQBFcigUAAOqjxw4AAEAR9NgBAAAogh47AAAARdBjBwAAoAh67AAAABRBjx0AAADMhGAH\nAACgCC7FAgAA9dFjBwAAoAh67AAAABRBjx0AAIAi6LEDAABQBD12AAAAiqDHDgAAAGZCsAMA\nAFAEl2IBAID66LEDAABQBD12AAAAiqDHDgAAQBH02AEAACiCHjsAAABF0GMHAAAAMyHYAQAA\nKIJLsQAAQH302AEAACiCHjsAAABF0GMHAACgCHrsAAAAFEGPHQAAgCLosQMAAICZEOwAAAAU\nwaVYAACgPnrsAAAAFEGPHQAAgCLosQMAAICZmPKMndfrraioaG5ubmpq0lbS0tJmz56dm5ub\nkpIidzYAAABZTBbsvF5vfn5+7+ZobcXhcFit1s2bNxPvAABAFDJTsPN6vampqUIIq9VaVFSk\nvda1tLSsX7/e7Xanpqa2tLSQ7QAAQLQxU7ArLi4WQhQUFJSWlvbempKSYrPZVq5cWVZWVlxc\n3Oc+AAAACjPTzRNlZWVCiIETm7ZV2xMAACCqmCnYAQAAYABmCnZWq1UI4XK5BthH26rtCQAA\nEFXMFOyKioqEEHa7vb9s53K57Ha7vicAAEBUMdPNEzabzel0OhwOLb39v/buHsaNqg0D6PVH\n+GmQaOm9TZQOCjQrauR1CdqGIhXe0m7otkyXxpEo2BUNrSVKrzsKpLWQQFQkjV1QIlFBg4gS\n/BWjjEYztjeQYMfvPadAWfvKmvswHj+eP6fanrn6DVDG43Gv19vD8gEA7NUhFbuU0nA47Pf7\n0+l0MpnM5/N6nyuK4vT01D2KAYBsHVixSyl1u93hcDgcDve9IAAAr5ZDOscOAIAtDm+P3cv1\n5MmTb7/99vfff98y5pdffkkp/f333ztaJgCAfyVgset0Oiml1Wr1PIO///77jz766HlG/vbb\nby+0WAAA/7GAxe4f+eCDD7777ru//vpry5hvvvnmyy+//Pjjj3e2VAAA/0LAYvec++pKt27d\n+vDDD7ePefjwYUrp9ddff6HFAgD4j7l4AgAgCMUOACCIgzwUu1wup9Ppo0ePfv755/KRO3fu\n3L59292JAYCcHVixWy6Xd+/erf/gRKl8ZDQaFUXx9ddfq3cAQIYOqdgtl8ujo6OUUlEU5+fn\n5b8ri8Xi3r178/n86OhosVjodgBAbg6p2N2/fz+lNBgMLi4u2s92u91er3d2dnZ5eXn//v21\nYwAAAjukiycuLy9TStsbW/lsORIAICuHVOwAANjikIpdURQppdlstmVM+Ww5EgAgK4dU7M7P\nz1NKJycnm7rdbDY7OTmpRgIAZOWQLp7o9Xrj8Xg0GpXtLdX2zNVvgDIej3u93h6WDwBgrw6p\n2KWUhsNhv9+fTqeTyWQ+n9f7XFEUp6en7lEMAGTrwIpdSqnb7Q6Hw+FwuO8FAQB4tRzSOXYA\nAGyh2AEABKHYAQAEodgBAASh2AEABKHYAQAEcXi3O9mXH3/88c8//3zx13n8+PHV1dU777zz\nv/9p1Sml9PTp019//fXdd98VSEkgbTJpEEibTBoE0vb06dM//vij3+/fuvWi5efhw4cvZZH+\nC4rdzd56662U0mg02veCAAAv5IsvvnhZL1XWg1eNYnezTz/99M0333z8+PFLebUffvjhq6++\n6vf7R0dHL+UFD91isZhOpwKpCKRNJg0CaZNJg0Daykw+++yz999//8Vf7Y033vjkk09e/HVe\nvhW7NZlMUkqTyWTfC/KqEEiDQNpk0iCQNpk0CKQtk0wcegcACEKxAwAIQrEDAAhCsQMACEKx\nAwAIQrEDAAhCsQMACEKxAwAIQrEDAAhCsdu1t99+u/ovSSAtAmmTSYNA2mTSIJC2TDLprFar\nfS9DXp48efLTTz+99957r7322r6X5ZUgkAaBtMmkQSBtMmkQSFsmmSh2AABBOBQLABCEYgcA\nEIRiBwAQhGIHABCEYgcAEIRiBwAQhGIHABCEYgcAEIRiBwAQhGIHABCEYgcAEIRiBwAQhGIH\nABCEYgcAEIRiBwAQhGIHABCEYrc7s9ns+Pi40+l0Op3j4+PZbLbvJdqPBw8edDqdtU9lFdFy\nuTw7O+s8s2m+WWVSrhvVZJfLZXtMVoE0lCtMO5Z8MpnNZp11GpnkE0ipPt9Op/PgwYPtYwJn\nsnb1qNRHRg5kxU6Mx+N2+OPxeN/LtWtXV1ebVrysIlosFmvfj4PBoD4sq0yKomhP9urqqj4m\nq0AaqrkvFou1j+eQydrJNjLJKpDVhvkWRXHjmJCZrF09KtWw2IEodrtQfYpXn1JVv2lso2Or\nv5caT+UW0WAwSCkNBoNqdtV8qwSyyqScWlEU1dSqtaUak1UgDdVMG5PNLZPyjbNlarkF0p7v\n8zwSO5O28ktjPoEodrtQfkQ1vg2sfTCqxWJRvrWKoij/0RiQW0Sp9ZV69Wy+1U67rDIp14rG\nVrXxKZ5VIHXl51D13mnvnconk7Vbj7rcAinfI40d22VNyXNL0taeafhAFLtdWPuhVW2s97VU\nu1Rufcr3zNpNs4hWz+ZbbY5l0kgg20Cqt0w7gdwySa3TFRoyDOTGeeWWSd3aaYYPxMUTu9Pt\ndtt/zufzPS3OTn3++eer1Wo4HG4flnNEKaXpdJpSun37dv3BbDM5Ozubz+eDwWBtAo0/AwdS\n5rDppMxSJplUp7fXrzpae6FAJoGUl4zcuXMnyWSDu3fvppTOz8/bT0UOZN/NMgtpw/eAGw8r\nhLR21iKqPrmrR/LMpN5gGodFMgykPDxUHWhr72nIKpNNV07UE8gqkPKQ640XT2SVSV115m7j\n8fCB2GMH+7dcLo+OjlJK9XPks1WdTDYajc7Ozva9OHszm81Go9FgMOj1evtellfCo0eP0rpL\njubz+dp9VJkYjUapdR1A5pmU7t27lzbsrotNsYM9m81mVavzEd7tdq+vr6+vr1er1WAwuLy8\nzLPbLZfLk5OToiguLi72vSyviouLi9VqdXFxUR1E6/V65S7eyWSy10Xbs8ViUW06ZFJaLpfz\n+bwoihw3qvvaVZiVTTt48/xfsOXiifbg8BGVl5Wk1nVtq4wzqatPNqtANh12bGy6s8pkk3oI\nWQWy5Xz/bDOpbLnKNXwg9tjtTuPe6OWfa2/Kmq3cIjo+Pr68vCxv3rbpa2VumTS0Z5p5IGvJ\npEEgbbllUu6w7Pf7mwYEDkSx24XT09P07JrHSvln+RQZRnR8fFxe9Xl9fd24PquUVSbtH/xJ\ntYMp5Z9ZBTIcDttfxOsXT5TDsspk7Uoym82yXUm63W5RFPP5vPFzWDm/cSplApluWne+jzBH\n4e9z/Y+s3Q2eW0TPczPMrDIpD0nXf3mimmyVUlaBrNW+KjarTLasJPn8qEBDOwGZrFq3aG4I\nH4hityOxf5nuH9l0fkNWEbVnWqmfMZNVJmsPguT847lta2+smlUma1eStT8hkEkgq9p5ut44\nlRu/OccORLHbnaurq2qrVBRF+2T5TGy5V1AmEW2/p0njVOhMMinVt7abJptVIA1ri90qs0zq\nPcZKUnqe+WaVSeMGkGsFDqSz2rrzAACAQ+HiCQCAIBQ7AIAgFDsAgCAUOwCAIBQ7AIAgFDsA\ngCAUOwCAIBQ7AIAgFDsAgCAUOwCAIBQ7AIAgFDsAgCAUOwCAIBQ7AIAgFDsAgCAUOwCAIBQ7\nAIAgFDsAgCAUOwCAIBQ7AIAgFDsAgCAUOwCAIBQ7AIAgFDsAgCAUOwCAIBQ7AIAgFDsAgCAU\nOwCAIBQ7AIAgFDsAgCAUOwCAIBQ7AIAgFDsAgCAUOwCAIBQ7AIAgFDsAgCAUOwCAIBQ7AIAg\nFDsAgCAUOwCAIBQ7AIAgFDsAgCAUOwCAIBQ7AIAgFDsAgCAUOwCAIBQ7AIAgFDsAgCAUOwCA\nIBQ7AIAgFDsAgCAUOwCAIBQ7AIAgFDsAgCAUOwCAIBQ7AIAgFDsAgCAUOwCAIBQ7AIAgFDsA\ngCAUOwCAIBQ7AIAgFDsAgCAUOwCAIBQ7AIAgFDsAgCAUOwCAIBQ7AIAgFDsAgCAUOwCAIBQ7\nAIAgFDsAgCAUOwCAIBQ7AIAgFDsAgCAUOwCAIP4PFTvcJzP/JooAAAAASUVORK5CYII=",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Simple Kaplan Meier plot\n",
    "mykm1 <- survfit(Surv(time, status) ~ 1, data = prost)\n",
    "plot(mykm1, mark.time = TRUE)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "1099f53b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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sFHjx7dunXrpRz5/PPPX9FYALACHDx4MJvN5vP5D3/4wyv229V4yJhEGHaXpaOj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\niMT/BWzwBBhVP0VQAAAAAElFTkSuQmCC",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Stratified KM plot\n",
    "mykm2 <- survfit(Surv(time, status) ~ treatment, data = prost) ## alternative 2 line chart\n",
    "plot(mykm2, mark.time = TRUE)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "9529582a",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Loading required package: ggplot2\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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2+dPh1CuDY8/J9+4Rd++rd/e2N/fxPq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\nTfwPl3kWpFFxtwEAAAAASUVORK5CYII=",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Advanced plot\n",
    "library(ggfortify)\n",
    "autoplot(mykm2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "40f4b98c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Call:\n",
       "survival::survdiff(formula = survival::Surv(prost$time, prost$status) ~ \n",
       "    prost$treatment)\n",
       "\n",
       "                   N Observed Expected (O-E)^2/E (O-E)^2/V\n",
       "prost$treatment=1 23        7     5.13     0.686     0.958\n",
       "prost$treatment=2 40       16    17.87     0.197     0.958\n",
       "\n",
       " Chisq= 1  on 1 degrees of freedom, p= 0.3 "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Log Rank Test to check if the two treatments are significantly different \n",
    "# In this case we get a p value of 0.3 which is not significant\n",
    "survival::survdiff(survival::Surv(prost$time, prost$status) ~ prost$treatment)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "845d4f1c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Call:\n",
       "coxph(formula = Surv(time, status) ~ treatment + age + sh + size + \n",
       "    index, data = prost)\n",
       "\n",
       "  n= 63, number of events= 23 \n",
       "\n",
       "              coef exp(coef) se(coef)      z Pr(>|z|)    \n",
       "treatment -0.69695   0.49810  0.53471 -1.303   0.1924    \n",
       "age       -0.08361   0.91979  0.03692 -2.265   0.0235 *  \n",
       "sh        -0.23664   0.78927  0.18511 -1.278   0.2011    \n",
       "size       0.06786   1.07021  0.02833  2.395   0.0166 *  \n",
       "index      0.77410   2.16865  0.18803  4.117 3.84e-05 ***\n",
       "---\n",
       "Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1\n",
       "\n",
       "          exp(coef) exp(-coef) lower .95 upper .95\n",
       "treatment    0.4981     2.0076    0.1747    1.4206\n",
       "age          0.9198     1.0872    0.8556    0.9888\n",
       "sh           0.7893     1.2670    0.5491    1.1345\n",
       "size         1.0702     0.9344    1.0124    1.1313\n",
       "index        2.1686     0.4611    1.5002    3.1350\n",
       "\n",
       "Concordance= 0.866  (se = 0.037 )\n",
       "Likelihood ratio test= 38.4  on 5 df,   p=3e-07\n",
       "Wald test            = 26.47  on 5 df,   p=7e-05\n",
       "Score (logrank) test = 34.47  on 5 df,   p=2e-06\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "### Cox Proportional Hazards Model - coxph function!\n",
    "### Cox takes into account the covariates like gender, age, weight, occupation, treatment, other diseases etc\n",
    "### It takes into consideration the baseline hazard + the covariate part (that is exponential), the changes of risk based on covariates\n",
    "cox <- coxph(Surv(time, status) ~ treatment + age + sh+ size + index, data = prost)\n",
    "summary(cox)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "55d4ca02",
   "metadata": {},
   "outputs": [
    {
     "data": {
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ERCsAMAiIRgBwAQCcEOACASgh0AQCQE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\nAAAASUVORK5CYII=",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Getting a plot of the model \n",
    "#autoplot(survfit(cox))\n",
    "#alternative way to plot would be\n",
    "coxfit = survfit(cox)\n",
    "autoplot(coxfit)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "de0bea54",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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yOfcl239VOkUikiWl1dbb0qIURvby8RZbNZ27arllkprOSsXIMVmqYphMjlGi2/\nUORv2G9XfYoxJmNbWVkJYrtoLeScRisvYxiGpmmNx1ZfOp0momKxmHX9JbZUtYySVlUIERI7\ngDVkMhki2r59u9wcGhoiopmZGfkg2Fn/3msulzt79myw2dvbG4vFqpbknCv5dr7eRoj6ZBtJ\nO8emqlVD3ubTNM33fSEE+QqalhljQghN0zivEiHaSDrOkrP6T85rVZ9ijHXxLiLK5XJ4ZyEU\nSOwA1jA3N0dE62p7+/73vz84OFh6yKuvvvp7v/d7webRo0fvuuuuqsfG43GF35hlo4sqsVis\nVj7aBLWxmaZpmqaq2rq7u4mouJokX0GXI03TZAMY51Vufl24cKH1UwAASBgVC9AMme1VNT09\nferUqd///d/fzHgAAAAILXYAzQnuzJaZnp6WHfLKWvj27Nnz9NNPB5u9vb2Li+WDgru7uxlj\n+XzesqzWI9R1PR6PLy8vt14VEaXTac55oVAoFAqt16ZpWjKZXFqq3sVnvbq6uoQQlmXl8/nW\na+Ocp9PppaUl3/ez2WyLLXZy2KbjOJZlaYuLVVvsAAAUQmIHsAaZwzUyEkJOiXLs2LHKkolE\n4qabbgo2l5eXi8Vi1Uo8z1PSNUf2FVPVy0f2rFcVm+wVpzY23/eVVCj7/zmO4/u+67pKbsXK\nqhzHCebpAADYILjKAKxBZmnBvVc5ALZ05IQk78CeOHECI2EBACAsSOwA1jY8PDw1NSUfT01N\nDQ8PlxXIZDKTk5PHjh3b9NCgA7j2yrnXvnXmx/8qt/xK2LEAQMThViyESfz6jDj7prd9R3Ho\ntrBjqWdsbGxiYkIuLBHMQkxE4+Pjd9xxx8jIyMsvv0xEhw4dKj3q8OHDlQ17sAV5XjG3/Aoj\ncq7HGnoAsLGQ2EE4/FiMETHPI68ozr7JPnGzn+oKO6h6xsbGKlebCNaWGBkZGRkZ2fSgAAAA\nLoPEDsLhfPa22PsZe+GieOMMETW95iwAAAAE0McOQpJM8j2fdK6+Nuw4AAAAogOJHQAAAEBE\nILEDAAAAiAgkdgAAAAARgcETAACXsfLv5Vd+7fs++X7YsQAArA8SOwCAy9jWvJU76yOrA4AO\nFFpiJ1fVJKLBwcFgMrAGy8h5YqUTJ05scKQAAAAAnSGcPnbT09Nnz549ceKETMsmJiYaLzM6\nOjo8PCz3Dw8Pj4+Pb2bkAAAAAG0rnMRucnLywIED8vGBAwdks1wjZeT665lGiAoAACAASURB\nVPv375f79+/f/6tf/SqTyWxG0AAAAADtLYTETuZh27dvl5tyMU2Zsa1ZZmho6MSJEwMDA5sZ\nMAAAAEBHCKGP3dzcHBHVT84aKUNE3//+9wcHB0uLXbx4cXZ2NtjcuXNnIpGoeqwQQtf1xsOu\nRQjBGFNSFRExxqhubEzTmBCNxxb8qyo2zrmSCstiE0L4LVTLOQ9iY4reCwAAgI7TLqNi5+bm\nZLNc42Wmp6dPnTp17Nix0jI//elPH3rooWDzySef/NznPle1tng8Ho/HWwj5Mt3d3aqqIqJY\nLBaLxao/x5m3vLiu2pLJpIKYLtF1XVUWS0SxWMwhIqJ4PM5ajlPTNE3TeLX3AiMcAQBgK2iX\nCYqDu64Nlpmenp6cnDx8+DBuywIAAABIm9FiJ5Mw+fj++++/9dZbiSiTydTJyWQOV6uMnAbl\n2LFjlc/efvvtf/3Xfx1smqa5sLBQVqa3t5eIstlssVhs5vVczjCMWCy2vLzcelVE1NPTwxjL\n5/OFQqFqAZ5dZaurDdamaZppmtlsVklsiUSCc14sFpX83jjn8Xg8l88ZRESUy+V8rfmGwHg8\nLoSwbduyLLfiHZfk+w4AABBhm5HYjYyMjIyMlO2cm5uTaZkcNlF2H1Y+VbWMvANba/q6eDy+\nY8eOYHNpacm27aolfd93XbfZ1/QRz/NUVUVEvu8zxjzPq1Wh77rc8xqPLfhXFd/3lVQoe+z5\n3od3SD3P81uoVt5plbGpei8AAAA6Tjh97IaHh6empmSiNjU1NTw83GCZTCYzOTlZ1q9uK/OF\n5u3cVetZrusslarVgnVZyfffYzk1DXsAAAAQlnASu7GxsYmJCbmAxPDw8NjYmNw/Pj5+xx13\nyOa9qmVefvllIjp06FBpbYcPH15z4EV0+fUGk2oaaVojo0192YAGAACRU/TtF1d/seSumoUY\nETm2Y/rax/Te68y1e7dDxwltVOzY2FiQzwXK1harLFP1ri4ow7nX21/z2XSaCeHn896l/n+s\nkGOKOvABAMAG+ZvF//wfFn50+T72d8sv/9Oe/yuUeGBDtct0J9AWGPN6ao4wYL29TAjK5bxc\nTu7hi4TEDqDNjY6OVh1qBlvHgrtKRDpp/UY3EeXcwrKbe8++GHZcsCGQ2AEA1OT79ur8S7a9\ndkfVMoxYsvtTicQnNiKqxlVdiRu2pmvMjz9604NE9Ox7L/zv7z0TdjiwUZDYAQDUtPT+33/w\n9tPNHbvw3n/s7vu3IV5mZR9lANhSkNh1GC+e8HdeE2xiOQWADeUUF4iIM00YfY0f5XmWay+5\nzorn2UQ1VpHZYDMzM8PDw/v37y8bbQYA0YbErtNw7htG2EEAbC16bODqWx5uvPzqwo8zs49t\nXDyNGBoaGhoaymQyVZ995plnfvCDHwSbjzzyiHH5hSUYKN/V1aVkRT65MLSS1ReD2JLJZK3Y\nuvTFhFhqsELOOWOs1sLizYnFYkqm/FQSm65pVLI2d0w3u0Q8LmKVb4fjOK2cCNoBEjsAgI2y\ncP6HmmZalpqVaRR65513/vEf/zHY1DSt1hrQmqbyzwTnKtexrBObXDlaVW1N4JwrfLEtxiZT\n4SAhvqv/1v/myt++o/fTCiKD9oPEDgBAMXZpGe5zs//nZftZuyzPvWfPnv379webtm2XNX1x\nzmUbnmVZSlrsZOJYaymgdWGMmaZJRMVisVarmGVZjS9+KITgnKuKTb5Sx3GUtNgpia1sFSLH\ncYpeserCla7r1krxoVMgsQMAUCzWdaNubrOtC5ftTF6X7G6XNpK77rrrrrvuCjbn5+fL/sxr\nmiYTu1wup2SZvlQqRUSrDS91XYcQQiZ2+Xy+VsaTK+QKVvUVtyuZpimEqLVC97oEiV2xWFRy\nW9MwDE3TWozNcV26PLHLu/lVUf29SCaTrZwLQofEDgBAMaF1XfPJx4kokUhommbbdj6fT1/x\n25yjgywAbCwkdtAW9J/9hOJx54ZBT0XfagAAgK0JiR2EKVjHVrz/HhGRZRX3/hdhBgQA0Mb+\n08o//4eLP7L89XW5s7xGuxtCBCCxgzD56W7n5lvY0hJfuMhyWWbj6gOg0sDAwIkTJ8KOApT5\nwfKPL7pNDrLu09Jqg4H2hMQOiIj8rrRnxoizzT+1PXgLERk/+bF4843NPzsAQAdxPY+IBmNX\nfzqxe10H6kz7zdQtGxMUtBckdkBE5CdTPgZCAQB0guvNq0Z69oUdBbSpdplUCQAAAABahMQO\nAAAAICKQ2AEAAABEBPrYAYQgFotVruotV3KMx+NyVv0WMcY45z09Pa1XRZeW+IzFYmVLxTeH\nMcYYUxWbXNrcMAwlFTLG8itzwbuzpOtExDlvbjp++XvTNC2ZTPb09FSdoHhxcbGFeAEALoPE\nDiAEVdeRTCaTjDHbtpWsWalpGudcySpJRJRIJBhjjuM0vv5mHUKIWCymKrZ4PC6EcF3XsqzW\na5OpWPAWyNW0fN9v7k0xDIMx5nmebduFQoFzBYuHAgDUgcQOIARVMyTZJuQ4jpKMxzAMwzAU\nJk+kLjZd1xUmdrFYjIhc11VSoRBCZ2Tbtu/7dGl5Td/3m8toZXrteV6xWERiBwCbAH3sAAAA\nACICLXYAEDVOcd7Kvd3csUKIeIyIqFiYy6+8Vmy2HgCAUCCxA4Cocd28bX3Q5LGcG1rKc/Pv\nvPq/elhhEwA6DW7FAgCUc+zFIKtjTHT1/2a48QAANAgtdgAANe286c9jqfUtygkAECK02AEA\nAABEBBI7AAAAgIjArVjobKxYZLlVKuR9IZhjc8tijuNr+GADAMBWhL9/0MHY8pL5w1PM83wi\nh4iITCLjxdPZg1/zdT3k4AAAADYdbsVCB+MLF1nFwlwsn+UXL4QSDwCAco7vhh0CdBK02EHn\nY8Tu/q+FEM7CRfqHH4UdDQCAMkfe/rdvWZn/bcfBbVp32LFAZ0BiB5HQ1880zfc8FnYgANAO\nzhU/eNPKBJs6E1cZHwsxnuY4vvtK7tdENFt4d1sKiR00BIkdRIiuuzt2eqkuPxYPOxQACM2j\n7019K/MdIr905293feb+K0bCCglg0yCxgwhJJIu37XOuvzHsOAAgTC+uvlq587U8lv2FLSHi\niZ1pmqZp1npKUzEphhBCCJFKpVqviogYY0RkmqYQovXaOOeMMVWxcc6JyDAM+YCIqGhRNtZK\nbLHYh4czIeTOYE9DLg19lb8uTdNisRhVe72+71fuBIAI+1T8hv+u704i+n+XX/7Ryk/CDgdg\nk0Q8sQMAgK0pJeLXmgNE1CPUfLk9vfrKTPY1n3ydaXemPzsYu1pJtQBqRTyxsyzLtu2ynbJN\nyLKsQqHQ+ilM04zH46urq61XRUSGYTDGLMvK5/NKatM0TVVsuq4LIYrFYi6Xk3t4Lseb/R3K\nls7gLTBcVxB5nmetp0Jh2wYREbmuq2ma4ziFQsGp8XrjcXS8A9i68n7xpewvqz6lWZrg3CoW\n6xzu+u6xD044vpwxk84W33v4qt9VHyVAyyKe2AEAABDRorvyF+f/fev1dPHEipfLegraBQA2\nAiYoBgCAKNsTv1ZX1IqR5sk7uj6ppCqADYIWOwAAiLKb49ccv3bc9pxaBUzT5Jw30gHG5Prf\nLP1npdEBKIbEDgBgq+vuLp/8Vo7QJ6J0Oq1kULkcTd/T09N6VUFsqVSqamy6rhORpmnJZFLu\nSTYQW5eeaOTsRs4gIs54UHlVsVis9d+bfWkxMdM05ekE50Sk63r9s9dnmmaKJ6q+F45TM/2F\nToHEDgBgq6scSSaEkOONLMvyKlZkboKcecqyrNar4pwnEgkiKhaLrltlHVUZsOd5lYPnqtI0\njTHWYGHXc4nI9/1a5eXsS47jyDBOLrz47z74geXVG5mxJsd15el88mk9L61WbEUqVh0+6Hne\n+uacgvaDxA4AYKuzLKuseUnTtCCxq5o8rZecN1TJXARCiCCxq5rfyIA9zyvWHegaYIzJIf+N\nFJaV++RXLR9Mz+k4jmz9+tuLL7aY1RGR6zjydJ7nyxgajLaMjM113aJbPbGDCEBiBwAAsFE8\n3yeiT8dvHEruXu+xru/95fzJDQgKogyJHQAAwMa61vz4Xemh9R7l+C4SO1gvTHcCAAAAEBFI\n7AAAAAAiAokdAAAAQESgjx20E89j2WzjxZmFUV0AAAAfQWIHbYQvXIydmg47CgAAgE6FW7HQ\nFrxUuulj/a7ySfMBAAC2JrTYQVtwbrjR7d/GmppL3e/tiysPCAAAoAMhsYP2wJjf169gQUoA\ngMh531n4g7efOO9cDDsQ6AC4FQsAANDWfpZ7ozSr26ah/wnUhBY7AACAtuaRT0QG6b975b1x\nZuyJXxt2RNC+kNgBAAB0AMH5bcmbwo4C2h1uxQI0ZGJiYnR0dHR0dHx8vH7J0dHRTCazOVEB\nwFZg+07YIUDHQIsdtMAw/K4mpynxhSDeMd8rpqenz549e+LECSIaHx+fmJgYGxurWnJiYmJz\nQwOA6Pu1NRd2CNAxkNhB87xEkhLJ5o5lmkbZFbo4rzakDTI5OXn48GH5+MCBA0eOHKma2I2O\njm5uXAAQZYLxneaV71jnww4EOknHNJkAhEXeV92+fbvcHBoaIqKZmZmyYjMzM8PDw8eOHdvk\n8AAgqhixh6/53X9z/ddGevaFHQt0DLTYAaxhbm6OiAYGBuoXGxoaGhoaqtW77t133/2rv/qr\nYPMLX/jCtddWH9dmGAZXcZOac84YSyabbFKtrI2IDMNgjCmprcHYnOKCY68yxszEVfVj0zQt\nqFCwhF+MtRKhYRiXHpixWPNVydiEELFYLJlMcm5UlsmuZ31kaBO257yU/WXVp+JunIiKRct1\nPSIq+MVWTmQw/fr4jp+L2VYqgS0FiR1AM+bm5mTTXYMymcxTTz0VbO7Zs+fmm2+uWlLXdV3X\nW43vknhc5aocmqZpmrKLRiOxreRft/PvELGe/t31S14WmxezjSopVOOCt0DXdaO1qoiIc24Y\nRjweR2JXR84rFLyGciDucbfIiGjZXuYuS4k4EVm+7fquLOD6Lm3cdOc+EdGKl/uL8/9+w84B\n0DwkdgDNCO7MNiiZTN50002lm45TPsxN5iWe53me13qEjDEhROVZmiOEYIxtfmyu67quS8Tq\nFK6MzXEc13Wbjo1zHlTleV7TVdGltknf9z3PcxxHSVtsVJ213nun+H4jJTnnKZYiomw2u413\n3xy/hoh+lptdcFZkgUV3ldhGZXY3x68xFvWiv471Dw3S9ySu2aB4AMogsQNYg8zhMpnMmndj\n67j55puffvrpYHN5eXlxcbGsTH9/P2Msn8/n8/mmTxQwDCOVSlWepTm9vb1CiEKhkMvlWq9N\n1/V0Ot1IbPmVFSufJWLs/TdqlUmn05qmWZYVNH3Z1gUr12QzGOc8lUoFb0E+n/NF8y1qiURC\n0zTHcfL5vFhcrNpiB604b188b2/qQlu7Y1cdv+aholfjmwajrlQXEeXz+eDbiME1neGvLWwS\nfNQA1iDzubm5OflADptY131YaJm/ulA+WuWj54pJIUSxWCwUCgrO5BYunv+nlYU3W68Kokpn\nmi6q//VkjKW0OBFx4TuYfA7CgMQOYG3Dw8NTU1MymZuamhoeHg47Itgo588+tfTBjz7aZrh5\nCuHjjBERx0QW0AB8SgDWNjY2tmvXLrnyxK5du4JJ7MbHx6enp8ONDdSyrfeJiDFNiGQ89Qkz\nsSvsiADok4nrd+hX3JX+bNiBQAdAix1AQ8bGxionJT569GjZnoGBAblABXS09LbPf+ya+8OO\nAuBDH9N6j+78vbCjgM6AFjsAAACAiEBiBwAAABARuBULAAr4vut7VskOxoXKuZEh2k4svvC/\nvHts1W10oh+5AIrvk8G0/7bvzt/u+vQGBgfQUUJL7CYmJk6dOkVEg4ODlR2VGimTyWQOHTp0\n7NixVmYXgxCxeMJLpoiIZ1fDjgVa5dpLqwsvB5uMa91X3BViPECNXWbbxF9eONncdHRZor9d\nfAmJHUAgnMRuenr67Nmzso/5+Pj4xMREZbf0Nct8+9vf3rSAYSOw3j7P84mIv/F62LEARE0j\nl9n2Iad8+4R59ee7fmPNwoxx0zSJ6IWLP/3n3BmPFKyGAhAZ4SR2k5OThw8flo8PHDhw5MiR\nyitO/TKYYwIAoI5GLrPtZrvRf1d67am/5eogRPRu9vw/584Q0d8t/fgHyz92Lq0Vu+jgJgBs\nXSEkdplMhkqW2pSTvs7MzJRO5V+/TCaTmZycPHbs2KFDh8oqdxyndMkjz/OY7ItRTZ2nGicr\nUVJVaZ1bKrbWKwxqUBUeQEdb8zJrWZZllfaJLP9vKDcX7JUlN9vKarkBubxW1q2+PpsrW90a\n+/9bViZjz/8/86cq2+16RFeDV4NOuVQqhEtlhIWQ2M3NzdGlZZqaK/Ptb387+CZa5vnnn3/o\noYeCzSeffPJzn/tc1ZKpVEp+51Oiv79fVVVElEgkEomEqtrUxhaPx+NxZZ3iZWze+11KajMM\nwzAMXu31+v5GrQgO0IbWvMweP378qaeeCjZfeOEFeXOzlOXZfT/6rzYowqp0Xe/qWsfV4Mpk\nPy1QkNL9y/7brzQ//O9vcv23ez7TpSUbr21dp16TwuskqY4tFoultVR/b5VLpW3bCk8EoWiX\nUbFzc3NrLr4py0xPT+/atWtoaEh+JQWANuR7zuL5v6v1rBCisJRYWVlppCaFUW1xjVxmw7XD\nvGJd5f9l/+29WteqkyeiHj31L9I3CywBB1teuyR2wS2D+mXkTdg6M/t/6lOfevLJJ4PNnTt3\nLi0tlZXp7u4monw+XywWm433I7qum6a5uqqmS0c6nWaMFQqFsrskzdF1PR6PLy8vt14VEXV1\ndXHOLctSstS6ECKZTMrYeLb63ZnGxeNxzrnjOJZleRXvuCTfd9hEdXIy/9IPbJ7Sy+y99957\n2223BZv5fL7s/7UQIpFM/N3QX+RyOSUN3rJFsM6V7QN7IcXj2QauBpxz2R7mWs5n9BtI/3B/\nIdfobCllDMPgnCu5sjHG5P0Wy7Icefu5NbquCyGUxEZEyWSSiIrFYtbKLvEql0rf93t6epSc\nC8KyGYnd9PT05OSkfHz//fffeuutRJTJZOrcJpAXoMoyL7/8MhGNjo4Gew4dOnT48OHga2hf\nX1/pvdelpaVaDcuu6yppc+ac+76vqvna933GmKrYGGNqYyN1vzdZm6xKa7kHj+d5nHPP81zX\ndXArAba8WpfQwM6dO3fu3Blszs/Pl2Vvvu9zxr/Y9y8W2IKSPnay60ud78C/pLfeKb7fSFVB\nqK7rKolN9sZWUlXQcU1VbEIIzrmSqgKe5zmug7uuUbUZid3IyMjIyEjZzrm5OXnFmZmZoUt9\newPyqcoyQ0NDQVWYxw4AoKpal9CQwwKAjRdOd4Th4eGpqSn5eGpqanh4uLkyAABQVcddQmPc\n7BKJBn/SWlL+xLgRduAA7SWcPnZjY2MTExPyjurw8HAwu9L4+Pgdd9wh2+RqlQEAgDV13CX0\nWnPgWrOh2y9CiN7eXiJa4ktvZ9/7ef6NDQ4NoJOENnhibGys8kJTtuhN1TKBgYGBOqMoAAC2\nuPqXUACIJIwMBwAAAIgIJHYAAAAAEYHEDgAAACAi2mWCYgAAgKYleKx02QnLs4s+5mmDrQiJ\nHQAAdKqEMHcYVxDRNcbHk+Kj5VlfL7zzloVlJ2ErQmIHAACdqlukuuOpsKMAaCNI7AAgalwn\n67lNLkDsewqWkAYACAsSOwCIlNWFH59/4wnPV7D+OgBAx0FiBwDNKObfzq/MluzwaxbdXPmV\nX7Se1ZmJa1TEAgCw2ZDYAUAzPM/127hVzIxfdeW1v9vEgYyzVKrf9tK+3y6pKgBA45DYAUAE\nMW6ayWubOJBzHkum7JUV5SEBAGwCTFAMAAAAEBFI7AAAAAAiAokdAAAAQEQgsQMAAACICCR2\nAAAAABGBxA4AAAAgIpDYAQAAAEQEEjsAAACAiEBiBwAAABARSOwAAAAAIgJLigGEgDEmhFjv\nU+vCOSciJVUREWNM1hlUyDmXp2g6tqYPr4oxJitkxErP0lxsjDH5khXGJoTgvMrb4bquqhMB\nACCxAwhBPB7XtOr/+xKJRCKRUHWi3t5eVVURUSwWi8Vi8rEhujVKtVJbKtXS4WV0Xdd1nYgW\ndJ2IhBCt1K82Nk3TUqlUb28v50blsxcuXFB4LgDY4pDYAYQgn88Xi8WynX19fYyxbDZbKBRa\nP4VhGMlkcmFhofWqiKinp0cIkc/nc7mc3FPILhZWV5qrjXOeSCRWV1eVxJZIJIQQxWLRsiwi\nKtpFInJdd2WlmfA458lksrljK8kM3rbtQqHA5uerJnYAAAohsQMIge/7vu/XeVbJKVRVVVpn\nUGH9l9BgbSqCqllhc/WXvkAFMZVU2/pvDABgTRg8AQAAABARaLEDAKiHi7hu9K33KM937ML5\njYgHAKAOJHYAAPVoek88vWe9R3luvoMSu8oRxMHwZ7UDqxWO+KbLh2mXEUI0Piw6GPTdemzB\nYOpWho2XVRiM+Fao1q8OvQUiAIkdhM+55noi4ivLfP6DsGOBtuP7zjuv/gnj+lU3HWEMvUc2\nRE9PT63pXdLptMITmaapsLaurq5aT6WzSylteV21qR0KHYwfV0J5bF1aquqQedu2FZ4IQoHE\nDtqA/OLIlU0bBlFSzL1j5d8hItt6z4htDzucaFpYWChrqtE0rbu7m4gWFxeVzLSXTCaJKJvN\ntl6VEKKnp4eIlpaWHMepWmaxsLhiNTq02TRNznk+n289NrqUbubz+VqxrYuu65qmqY2tUCgw\nz5v35quW6e/vV3IuCAsSOwBoU07xwvKF523r/Q+3cZNow1SO2FU4/LlqtaoqqVXhusJWOIQ8\naPhsw99bWYW46xpVSOwAoE29/9b/nV3657CjaBIX8e4r7kqn04ZhWJa1srLCOK63m0cwrrGP\n+pD55Lu+F2I8AJsGFxoAaFOOvUhEjOm+35H9fhjXLv24yOo22fXmjuvNHcHmefviT3OzIcYD\nquzbt4+IXnjhhTVLHjp06Pjx43UaJhuvqrNE/Fqj63qtMVNy9aHWaZrGOVfVT1Y242uapqRC\nTdMYY+0ZmxCiLDZmmcxocl7+YO1RwzA0pX2WIXSx5HX51dfCjgIAoDNEPLGTWVfVp+rkfOsi\nx6KrTZ7aObY6v9ImarsstoLpN5ttBzMpyBdcWQC9STaU6yy//9ZfftQZjogxluz+dN+OL4cY\nFQBET/Qa2JSLeGKXz+crB29v27aNiHK5nJIVOU3TjMfji4uLrVdFRH19fXJwlpIxUIZhpFIp\nVbH19vYKIQqFQrBaaCvkmLvS2PjyMm92xFwikQhW5HRqvF75vsNGWL3449WFl8p2FrJvpj/2\nRU3vDiUkAICtCZNCAUCrfM8iIs6MvoGRvoGRdP8+uZv8osKzvPfGX7z96p9U/rz+8h/+8h9/\nf/YnD8nNlfkXFZ4UoNQdXZ/6QvrWTyd3hx1IJzl06BBjbHb2sj6OjDHZxY2ITp48uW/fPnbJ\n448/HhTbt2/foUOHHn/8cfnU7Ozsvn37ggPrH1sWgDxjWRilZmdng5K1quoIEW+xA4BNw4TZ\nf9V/T0SFldeW55XdLhFaiogR+Vb+3fUcVXPqWtiCurXULfHraj0bj8c1TVvx1573zmC6YJyj\nTWQ97r333uPHj//N3/zN17/+dbnn5MmTRPQnf/InRPT4448/+OCDpeXlZlD4lVdeOX78OBHt\n3bv3hhtuKC255rF0aQiFfHz69Ondu3efOXOmrB4imp2d3b37snz9wQcf/MUvfnHs2LGmXnSY\nkNgBQFvTzSs+ft3vFfPv1Cyg64xxz3Ud99J8sEx09X9+k+KDThBjxnajZmeMhJnQNG3ZUrkq\nBgTuvvtuIvrFL34R7HnmmWeC/TIVC5ItmWB997vfDZKz06dPP/bYY6W5WmDNY4no+PHjQQGZ\n5D3yyCOV6dojjzxCRKUnkoXvvfdeGWcHQWIHAO2uq39fnWeTyaQQolgsKuk1WyrV9zlGnHE1\nI+gBtqyDBw8eP348SKeOHz9+8OBB+ViObJudnT158uQzzzzzyiuvVB5eNatr8NjS9rljx47J\n9r+yxG52dlaGVHoiWfiZZ55BYgcAEBFC62JMwfh0gC1O3o09efLk3XffLe/D3nvvvfKpynug\nZfbu3VvrqTWPJaKyu65f+cpXTp8+PTs7W3k39vjx48FN246GxA4ANsqFd7/LeZXZZzhjmqYX\n7TWGVjjF6mtZAkBnufvuu/fu3Stbv775zW/u3bs3aAaTmdnBgwdvvvnmG2+8cffu3WvmaoFW\njm3Q6dOn1Va4CZDYAYBql1ZZWJlXcU1kuBMK0PG+8pWvPPjggw899JDsMyd3yta7Z599tonb\nnQ0eW9Y4993vfpcqmvGkWj35Og6G9gCAYmbi2nT/PjNxba2fWPK6RNcNdQoEP4n0nvQ2DIMA\n6Hj33HMPXRqjIB8H5FgKIpKzmayr2jWP/epXvxpMcXLo0KHTp08H3fsCN9xww969ex988MHS\nKU5OnjzJGDt06NC64mkHaLEDAMUY41de9z/WKSCESCQSKytrzy4BANEgk6fjx4+XzloiG9sq\nO7c1cgO0wWNvueWWsvuzVWcweeqpp3bv3v3ggw+WzZ/y0EMPrRlJu0GLHQAAAGy4r3zlK8G/\ngTNnzgTDI/bu3fvss8/KFrU6Mwmv69hjx44FTXQHDx6stbzkDTfccObMmdLGvIMHD1ad8a79\nsWivobm0tFRrSbHV1dW2XVIsm80qXFLs4sWLrVdFl5YUy+VyCpcUm5//qHc8X17kH7xf55A6\n5JJicsIL5/obq5ZpqyXFlpeXi8XyoQP9/f2MsU559wvZNwurZ+Tjxfee/eCdfye0rus+8380\nUpvaFju1051wzlOp1MrKiu/73R/7QoujYtPptGEYlmXVf7Ghfzjnz1gVcwAAIABJREFU5+fL\n/hZomtbT00NECwsLruu2fopUKkVEq6urrVclhOjt7aUaV/gmyAvI8vJyg+UvOEv/lH2t6lOM\nsa6uLiLK5XKO41Qtsy6GYWiapuSqS0TpdJqICoVCzNVvT+2pWib0TyO0CLdiAWDdsgs/futn\n/7NdvCA3PVdBJgoAAK1DYgcA6/b+2b/MrfyibKem94QSDAAABJDYAcC6+b5DREZsoGvbb8k9\njFiy59OhBgUAAEjsAKBZuvGxvoGRsKMAAICPYFQsAAAAQEQgsQMAAACICNyKBQAA2EADen9K\nJJo7NhaLvWO/r2ayE9gakNgBAABsoI/pvVfqfc0dG4/Fz3sLauOBaENiBwDr4Pu+7xV832VR\nntocAKBTIbED2KKc4nx28acNFnZzKc65ZVlW0fI9x7Y+8NmGRgcAAM1AYgewRfm+J6eja6yw\n4/vc9x3fU7BKEgBsHaoWDywjl26DSkjsAACibHR09NixYwMDA2EHAlsXP/MrtRV6uwfVVhgl\nSOwAACJrYmIi7BCgLVxlfuxGc+e2bduIaHV11SpYYUcEGwWJHQBANI2OjoYdArQLRqQxoTFB\nRBoTDsMstpGFxA6gIRMTE6dOnSKiwcHBo0ePNl2mfaxcfHFl/oUGCxeWTc6Y7TiO4ya7P7mh\ngYESMzMzw8PD+/fvP3ToUNixAMDmQWIHsLbp6emzZ8+eOHGCiMbHxycmJsbGxpoo0z4WMn/9\nxsz/0NyxQuuKpz6hNp62kkzfQEbc933GRNixNG9oaGhoaCiTyVR99pVXXnn99deDzS9+8Yuc\nX9aEI8SHr900Tc/zWo9HVhiLxVqvKgjVMIwgzlZomsY5bzw20y4YttFInR+WN82Y0eQLl/UY\nxhqnW5NhGMEL1HW9VjEl7zWEC4kdwNomJycPHz4sHx84cODIkSOVSVsjZdpHYfWNpo91nRXX\n2ZBhbm2Cc1NoKd+P8kx9zz333FNPPRVs3nPPPaZpVi2ZSDS5ZEJVdVKKJsTjcYW1pVKpBkvm\ninbMWSNRK03Fkslkymy08ko8t46ks5ZEPBG8QNM0a73dtm23eCIIHRI7gDXINo/t27fLzaGh\nISKamZmRDxov04Z0Y9s1n3q8kZKpVIpzfvH9mTd//ucbHBRsBtM00+l0sOn7fmUiyxiTT21q\nZI1RHhtjrPHaqv66Squiy2OrX77BM7ZyeBDDmr+39ny7YV2Q2AGsYW5ujojqzxaxZpmf/OQn\nf/iHfxhs/vmf//kdd9xRVoYxNvP3I4vnG+331grPLcgzNjgXlPx7oGsfNrcITSMiTdeankqq\n8VM3GJthGApbg/r6mlwAqoyMzTTNOrfS5ufnWz/R9PT05OSkfHz//fePjIzUL3/w4MGDBw+W\nxrC6ulpaQNO0np4eIlpcXHRdt/UIZXNR2VmaI4To7e0louXlZSUtTIlEQtO05eXlBssvOEsr\n2eqN1sEHO5/PO86Hkz4uuAuG3uSM3vF43HGc1qeCWyrG5615OSo2m80WCoVaJWUZ6FxI7ACa\nMTc3t2ZrXGkZx3FK/2w4jiP/5Jdx7VW7uHnrQhpmX9Uw1uQ5WfmgucNbP3ajK2zn2KoaGRlZ\nM5kDgK0AiR1AM4K7rg2Wueqqq772ta+Vbmaz2bLyiURi540Hez/+XyppIOGcCyHqtGd4bs6I\nDdT54l7KNE3GWNCxOrf6FhF5rtfg4ZWx6bpuWWpm0pKxOY4TNJC0QnZ4z+VySu5JxWIxIYTj\nOKpeLABAfUjsANYg87NMJlPnTuuaZQYGBr761a8Gm8vLy/l8vqxMIpEYuO5fZbPZyqeaYBhG\nKpW6ePFirQK29UF28SfFYrHB2hhjevxqTe9x7EUiYsTi6U82eHgZIYSu680dW0nXdSGE53lK\nKpSJXT6fV5LYydhc11XyngIQUZybOlv33+4Yqz5aAqIHiR3AGmSuNjc3Jx/MzMzQpeER6yrT\nbriIGfG12x2lWDLNOSex7cbPfbeQe4uIOBNMKJi6AjbUwMCAnIIHFOrTun4r/ZmqTzHGZAfN\nZf2j/n9N5GF1XG/u2G6gG9waZmdnd+/eHWw+9thjX//61+XjoF/Es88++6UvfSn4Crdv377T\np0/Lxx09iCS0xK6V6V47axpYiIDh4eGpqSmZqE1NTQ0PDzdXpq0IrSuRvqXBwl29vUIILZcj\nbdEufrChgQG0OU7crLFyA2Msxg0iKnKDb2y/ys7D3nqDn32zxUq8Xdf611y/ZrHdu3c/++yz\nd999NxE9/vjjDz74oEzsGGNBklfa83Xfvn233HLLCy+8IMvv27dPPu5E4SwqEkzlKr9KVl3N\nsFaZiYmJq6++Wu7ftWvX+Pj4ZkYOW9PY2NiuXbtGR0dHR0d37doVTFA3Pj4+PT1dvwwAABAR\nW82y9zKt/qyW906uNDs76/u+zOqI6J577pE7T548SURB091jjz0mH5w8efL06dPHjh2Tm1//\n+tdPnz4tC3eicFrsmp7uNZPJnDp1Kvjty9Vy6nd+AlBibGys8lNa1mBctQwAABCRn077O3e1\nXsmaZW644QYiOnny5Je+9KXS/a+//vrevXuDzXvuuefBBx+U+6li6Prrr78epIadJYTErpXp\nXolocHAwSOPQfQQAAKAj+Fdf4159zeacS2ZpZ86cueGGG8r621W1d+/ezr33WiaExK6V6V7n\n5uZ27do1MzNz5MgRuacssfuHf/iHP/uzPws2H3nkkc9+9rNVT5FMJpPJ5PrDr4Ix1t/fr6oq\nIkokEqqW8dmI2FQt41MWm8/JLzQ5crB0ilpe7fV2dE9YAABo3MmTJ0sTtTNnzsgHN954YzA8\nonL/7OysbOrrdOH0saskM7k1y7z99tunTp168cUXZR+7w4cPl/Wxs217uYTruqyCLFm5v2kK\na2v/2NRWqLCqNWNr9TMKAAAdQiZqRDQ7OxvckA3GUsjN0v179+4NZqQ6efIkY0we3onaZbqT\nBqd7ffvttwcHB4NuTENDQ0eOHCm9jXv99deXTgN7xRVXVE4DKxvqLMtSMp2ppmm6rquapCqR\nSDDGisWiknVyNE0zDCOXy7VeFRHF43HOuW3bqmYLi8Vil8WWy7GmZrslIsMwOOeu69q27Ve8\n45KqBloAAGhnd99998GDB4Pbr2fOnNm9e7e8LSsXzJVd6x577DH5gIheeOGFffv2BU0AsnAo\nwbduMxK7skUMb731Vmp2uterr766/rmuvvrq0mlgl5aWKlMu+Qfetu3mJs0vY5qmEEJVYheP\nxxljtm2rmqJWYdIZi8WISFVsmqbFYrHSqrhl8WZTRk3TZGJXLBadGuEhsds6GNO51mSHAc45\nF5jKFaCzHTt2LBhnSZf3xgkeyzu2wX70sVuHqosYNj3d6+TkZNnAw0Za+wBg6zDiV8a7bm7u\nWCGEmehdzc+rDQkAQifHyQatcd/85jdvuaXRuTw7SDh97ORUrv8/e/ceG9d15wn+d86599aT\nL1GyQ0kx/SAVOlIwjaZjO+Joe5NOmiENct3OoLkP97r/sYSA7pY6veYaWGO1WgSIlwE6FmAG\nQxMDjNfuwTCYpHtIRAzRjXZ3a6S1esKkJ7EdR2ISy7GqbNmSSBbreV/7xxGvyvVise4lq+ry\n+4Fg1K0699wfyeuqX52nfFx5udeCMv39/X19fc7KYfPz8/mTZGE3EsJs76DOvdS5197TabZ3\nEOZJbCdGjIjJ0Yz1jgUAYAuGhoZefPHF3t5eOfD6yJEj+a16vlGfxM7Ncq+Tk5Pnz5+Xz58/\nfx47T+xytlDszn1s3938rk+xfXfbnfsICcd2Ylxtv/sr7Xd/JRBp1gEoALBrnTx50t7gy6yO\n6jh5ws1yr0jmAAAAAIo1yqxYAGh27JO7Z9q2Va9IAAB2LSR2AOABRdsT7XjIObRtY/X639cx\nHgCA3QmJHQAAQKNrFZHPhu4lohDHcjxQCRI7AGhcXIQ514jI0FfqHQtAfXw2fG+X0a4ypVVg\nMU7YHBI7AGhcwch9WugAkb3y4d/WOxaA+tindWhqo+z/WRurt6/eIewiSOwAAABgG92M/8jb\nCvd0fdXbCv0EiR0A1EJRWwPhTzuHAp1EAAANAIkdANRC0ToVrbPeUQAAwCc0d7c9AAAAADiQ\n2AEAAAD4BLpiAcB7jIloR3+5VxVFaWlpsZVbm9YjlKincQEA+BwSOwDYDqzCCDxVVbVgq6Kh\nxwAAwGNI7KBRWC1tVrR1q2fZRGw7ooHGwtru+lK519rb2xVFyWQy6+vrTvmdCQsAoNHgGzM0\nDMaI863+Yxz38K7AmLKVf6Le8QJA3SwvLzPGlpeXqyy/sLDAmH++DaLFDgAAAPyjp6fHtu16\nR1E3aO0AAAAA8Am02AEA7HahUKighYNvDHIIBoOWZbm/hBCCMRYKhdxX5cQWCAQUxYNPMVVV\nvYrN6dHTNE0ID4YEqKrKOfcktvw6y/U8evK3rrvl5eXe3t4rV64QUW9v77lz54aHh+VL586d\nGxoako+dX8KLL76Yf/rAwMDFixflY/n/xdmzZ0+dOnXlypWenh554osvvnjy5Mkd+Wm2DIkd\nAMBupyhKwSe9c6iqqie9WjLL0TTNfVVObIqieJI8eRibQ1VVT2LjnHPOvY1NURReZnSyYRge\nXqjAykf/uPbReZeVtO471r7v97Z0yje/+U0nPxseHpaP85Oz/Jt/YGDgyJEjFy5ckOUHBgYu\nXLhw8uTJt99++9vf/vb09PSJEyeOHz/esFkdIbEDAIBEIlGQvSmK0t7eLl8yTdP9JaLRKBHl\nzVyunRCio6ODiJLJpK7r7isMh8OKoqytrbmvijHW2dlJRMlkMpfLua8wFAppmra6uuq+KiLa\nu3cvEaXT6UwmU+GKnlyrmJG5vr7yM5eVhFs+s9VTnn/+efngscceO3Xq1PLysmzMc5KzF198\n8dSpU0S0sLBw8eJFmdXJAqdOnVpYWBgaGnr22Wd7e3sff/zxl19+ucEH8CGxAwAAgG2nhQ62\ndn7BfSVbPaW3t7fgmcuXLx89etQ5lAmffJ4+2YAnnxwaGurp6XnxxReHh4fPnTtXS9w7CIkd\nAAAAbLvWvV9o3es2sdtuR48edVrsCrz99ttE9Dd/8zfOKL3GhFmxAAAAsIscOnTImR5BRLJn\n1nm+5AJ4CwsLshP25ZdfXlhY2KFAa4LEDgAAAHYR2eR24sQJeejMmR0aGjp69OhTTz0lD+XC\nxTLPczph8+fYNiYkdgAAALC7yLY3xpicHus8L/th5fPDw8NyiZMTJ04cPXpUpoMy+XOSwgaE\nMXYAAADgH/k7T+TPYC3YkSL/cf7yJcVj7Kanp/MPyw3CaxBosQMAAADwCSR2AAAAAD6BxA4A\nAADAJ1iDL6Ds0urqqifrkoMPyCXXG8Ta2ponq9KDP9T95rxx44a/Pwugep7fjYlE4mb8R97W\nuafrqy0tLd7W6Rs+nzzR1tZW7xAASmhtba13CAB3yF2wAMAH0BULAAAA4BNI7AAAAAB8wudj\n7AAAAKCOEonEdlSLMXbloMUOAAAAwCd8PnkCAAAA6utHt97wtsKvdjzqbYV+ghY7AAAAAJ9A\nYgcAAADgEz7viv3ggw8ymUy9o4CGcO+999Y7hDuuX7+eSqXqHQU0irrfnFevXsVEOpDqfjeC\nSz5P7HRdx/r+0IAMw8CdCY0jl8shsQPwB3TFAgAAAPgEEjsAAAAAn0BiBwAAAOATSOwAAADA\nP5aXlxljy8vLlctULrB9tvvSSOwAAABgF1leXu7t7fXrpZHYAQAAAPgEEjsAAADwIdknu7Cw\nwDYsLCw4bWa9vb1nz56VJQcGBpwy+eeePXs2/0mn2IkTJ/IvtOnpAwMDlNdcl39pz/l8HTsA\nAABoBP+49i/nV//FZSXH2n7n91p/Z0unfPOb35TLNJ49e3Z4eNi27StXrvT29l65cqWnp4eI\nBgYGjhw5cuHCBVlmYGBAPiait99+21niMb8YY+zxxx8fGhqqfPqpU6fk6QMDAydOnJieni64\n9HZAYrcrXLt27cknn3zttdcOHDhQ71hg98J9CO5du3aNiDy5hTysqo6XaCLXc7d+lvqVy0o+\nE+re6inPP/+8fPDYY4+dOnWqYOLCwsLCxYsXnVTs5MmTp06dWlhYkE1rjz/+uHx+eXn54sWL\nr7zyijx0sr3Kp587d04+/8orr/T29j777LNbDb4GSOwAYIccOHDg9ddfr3cU0MSc7wYNVVUd\nL9FcDgb2faHliPtKtnpK5ckKly9fJiKnC9V50ukzlc9cuXKFiIqb2ao8XZ4om+u2Gv9WIbED\nAACAbfeFliPuE7vtcPToUafJzVH9iiQuT/ccJk/4zbVr176Y59KlS85Lb7zxRsnnATxX8j6U\nT167dq3g1YJ78plnnnGerOsPAY1FNoAR0ZNPPvn9739f3kXf//7382+VkjdPwf0mzy2u6tKl\nSwVlSr5hFl+i+PRLly4VXGLHfkuwVYcOHbp48eKmeZhsaSsuVvl02c7nnCjH5G03JHa+4rT8\nv/7666+//vprr7323HPPOW9Jr2945plnnnvuufqGCj5W+T6kjT5Zx+HDh0dGRh555BEieuaZ\nZ+6//37nRn3mmWfq93NAYzlw4IDs1nzttde+9rWvySevXr0q7xYqf/M8+eSTL7zwgvP8Sy+9\nVLKqV199Nb/Mt771reI3zAr3Z/7pzz33XMlLQINwOkaJaGho6OjRo0899ZR8SU6hLU7Uenp6\njh49+u1vf1seyskQm54+PDwsHzz11FPHjx8vuPQ2QWLnQ85AXfnxKT8vieiP//iP5YNHH32U\nNkb1AmyTcvdhgb/8y78kom984xtEdOnSpbfeeks+JqKvfe1rb731FlqXoQK5igSVv3muXbuW\nf/tVePcreIcsfsOsfH/iDba5HD9+fHh4WCZnzkRXxtjw8HC5KasXLlx48803ZbEjR45MT087\nz5c7/cUXXywun3/p7YAxdr5y4MCBkZER2UEwMjLivAFJBw8erFNcsLtUvg/zff/735+fn3dm\nVLz//vtEVNAD+/7775dLCgGct7XKN8+lS5c27aYoeIcsfsMsdwlZEm+wjaOnp8eZteo8KHh+\nenraybRoIzkrV0mFYpWff+yxx06ePFnwZMGlPYfEzm++8Y1vyM/RL37xi/Pz80SEeYiw86q5\nDy9duvTSSy8VzBk8fPjwSy+9tGNxgp+Uu3lkKibX2XGGvnl4CTTOQUNBV6xvOeNO0JMFdVTu\nPpQtKAVr2h08ePCtt97CxyTUoNzNc+nSpcOHD7/++uvyTpOtbt5eAqChILHzFTktyzmUb0Do\nIIAdtul9eO3ateeee+6FF14oWLj1kUceOXz48Le+9a38evA5Co4KyVmFm8fJxuSNt2lV5Wz1\n/nSfSkLzkj2527e9RAXoivWVRx555IUXXsj/THV6H+oYFew2m96Hs7OzRFQw5kmWeemll+Ry\nEvlP7lTg0ARGRkaee+65kZGRsbGxgpdK3jxyxKfT/fraa689+eST77//vny+XFXllLxEhTdY\n5xIVRpoCeIsVjw30k9/+9rfpdLreUUBDOHToUL1DuCMWi62vr9c7CmgUdb85r1y54u/PAqie\n53djIpH40a03vK3zqx2PtrS0eFunb6ArFgAAAMAnkNgBAAAA+ATG2AEAAMA2+mrHo/UOYRdB\nix0AAACAT6DFDgAAALbRj1bXvK3wq22t3lboJ2ixAwAAAPAJJHYAAAAAPoHEDgAAAMAnkNgB\nAAAA+ITPEzvLsuodAkAJuDMBAGA7+HxWbHt7u67rBU/u3buXiNbX1zOZjPtLBAKBUCi0srLi\nvioi2rNnD+c8mUx6shOapmnRaPTmzZvuqyKijo4OIUQqlUqlUu5rUxSlra3txo0b7qsiora2\nNlVVM5lMs+zT1draGgwGC57s7OxkjO2Gv76qqq2trV799dvb2xVF8eqvL4To6Oi4ceOGJ1ts\ntba2apqWzWYTiYT72rbPnj17Cn5eRVHa29uJ6NatW6Zpur9ENBolIg//RkS0urpa/A5fg3A4\nrCjK2poHMzcZY52dnUS0traWy+XcVxgKhTRNW11ddV8Vef3xB43J5y12AAAAALsHEjsAAADw\nv+XlZcbY8vJyvQPZXkjsAAAAAHwCiR0AAACATyCxAwAAAF+Rva6OhYUF56Uf/vCHJZ/3DZ/P\nigUAAIBG8I+J9fOJpMtKjrVEfq8lWrnM8vJyb2/vlStXenp6nMNz58719vYS0fe+9z05B/zs\n2bPDw8OezH9vKEjsAAAAYNtd142fpdyu5fSZYKDKkjKrkw9k9ianTTz//PPy+ccee+zUqVPL\ny8tOSX9AYgcAAADb7qCmfiEacV/JpmV6enqOHz/OGCOi48ePT09P578q2+18DIkdAAAAbLsv\nRCPuE7sqTU9Py3yOMfbyyy8Tkf+6XMvB5AkAAADwJ9u2ZUrny3kSJSGxAwAAAP9YWFiQ/bCS\nHFrn+x5YB7piAQAAwD+GhobOnTuXn9vJGbK+33NCQmIHAAAAvjI0NFQ8qM6ZHlvy0DfQFQsA\nAADgE0jsAAA+YTVNH6yJD9ZEvQMBANgyJHYAAJ+wnqFbKXErJUyLiMiHXTUA4F8YYwcAUNrl\n6xoRtYWs/W1GvWMBAKgKWuwAAAAAfAKJHQAAAIBPILEDAAAA8AmMsQMAAIBt9NW21nqHsIsg\nsQMA2O00TSt4RgjhvGRZlvtLyAoDgYD7qji/3dekqqrz2A1FUTjnnsTm7Hagqmr+zgc18zC2\n/DrLVejJ37rYWzGPk43D+zGfqSwkdlA3pm3rts2IFC/e/gCgZuFwuOAZJykJBoOeXEJmYMUX\nciMYDHqyc8B2xBYIBIrT5Rowxhhj3samaZqqqiVfMgwkTE0PiR3Uzc+TyV+sJxnRV1qi9Y4F\nYFdbWVkpyJAURWlvbyeitbU10zTdXyIajRLR+vq6+6qEEB0dHUSUSCR0XXdfYTgcVhRlbW3N\nfVWMsc7OTiJaX1/P5XLuKwyFQpqmra6uuq+KiPbu3UtEqVQqk8mUK+Nt6yDsPCR2AACVZA12\nM7XlXSgY2R3hbenVAgCoAIkdAEAlGZ1l9C0ndqpAYgcAdeDzxE5VVWcIcPFLnlxCjmz1ahiK\nHNeiKIonFSqKwhhrzNiEEMw0NU1jXgzikUNkhBBe/bAAAADNyOeJncy6Sr5UIefbEjmy1dvk\nqZFjq/Ar3XJt6bRMr/+/TJaIDgYDvbWGumli58kIawAAgAbn88QunU4XD62tZvRo9QKBQCgU\nWllZcV8VEe3Zs4dznk6n0+m0+9o0TYtGo17F1tHRIYTIZDKpVMp9bYqi2EIkk0kiShIRUTCT\n2Res8S/S1tamqmoul6swNFv+3Tc1NTW1uLhIRH19fZOTk1sqU825AAAA2wc7TwDcMT8/f/Xq\n1bm5ubm5OSKampqqvszU1NQ999wjn+/u7p6YmNjJyAEAAAiJHUC+mZmZsbEx+XhsbEw2v1VT\nJh6PLy4uPvTQQ/L5J5544p133onH4zsSNQAAbG55eZkxtry8XO9AtpfPu2IBqifzsP3798vD\n/v5+IlpaWpIPKpchor6+vq6uLvl8V1eXbM9zZLPZjz/+2DkMBALlhlEyxjwZYemMO3RfFW2M\nsOScN2Bskpe/N4s45y7HZXJuCyHk761ybJ6sEgcAm+rp6dkN462R2AHcFovFiMhJzrZUJhaL\ndXd3Ly0tnTlzRj5TkNj97Gc/+/rXv+4cTk5OfulLXyp5iXA47OEq83IdV68Eg0EP5x17G1sg\nEPBqYdX1WxSJRFxWoink/HyaplXYhCA/4wcAcAldsQCVyExu0zLvvffe4uLiG2+8IcfYnT59\nGmPsAADqRfa6OhYWFiivK7bg1fwyRDQwMOA8WdcfokZosQOoxOl1rVzmvffe6+vrGx8fl8/0\n9/efOXMmvxv38OHDr776qnNKR0dH8WzltrY2xlg6nc5ms+4jV1U1FAp5sksSEbW2tnLOM5mM\nJ3PJFUWJRCJe7ZLU0tIihMhms57MJeecE7XK+dpu5IS9smJEIhE5X9uTueQATe3KdXH5utus\n49BdRu9dm4xeWF5e7u3tvXLlSk9Pj3N47ty53t5eWaCgT3ZgYODIkSNDQ0PO4wsXLhDR2bNn\nBwYG5OMmgsQO4DaZw8Xj8Qq9seXK3HPPPZUrD4fDDz74oHO4trZWbh9Jy7I82YdbjmPzaktv\n+SboVWzye7C3sdm27UmFcjCcZVlux9iRbRiGt7EBNLW1DL+24raf8FOtnKiqYakyq6O8NK7k\ntIkTJ04Q0fT0NBEtLCxcvHjRyeROnjx56tSphYUFmfM1CyR2ALfJXC0Wi8kHckpE/syJymVm\nZmacFjupmtY+AIBdoj1s3b/X7VSh9ip26uvp6Tl+/Lj8Ann8+HGZtJV09uzZl19+2fkWd/ny\nZdr45um4fPkyEjuAZjU4ODg7OysTtdnZ2cHBwSrL9Pf39/X1zc/Pj4yMENH8/Hz+JFnYhQyL\nXf5QjaxzRSFd56mU+sA+XWBUM+xiD+w1H3Cd2FVpenpa5nOMsZdffplK7T+0sLBw6tSpK1eu\n5D959OjRput7LYC3GYA7xsfHu7u7R0dHR0dHu7u7nRa4iYmJ+fn5ymUmJyfPnz8vnz9//jx2\nntjlbJtMmxkWyX+mzXbBMgsADce2bZnSOXMjpIWFheHhYWccnnTo0KGLFy82+0J3aLGDRnHT\nNN/MbHnSQJCxnkDZhSRqMD4+XtCjSkQFWVrJMsXFAABg58mkzWmik4maM3NCPjM8PHzu3Ln8\nrI6IhoaGjh49+tRTT8lGu5LJX+NDYgeNImlZSWvzwRMFWjj3NrEDAGhkzKxy8sAn2ILIyxXB\nG9rQ0NC5c+fyh8rJ5Mxpivv2t79NRMPDw/lnyTIXLlyQy53kP7lTgXsDiR3cYdt2hRaztGUJ\nxtKWldn4GiSI1OZc5gcAoEmxDy22uuV+fbuDW5/aRW/XQ0PYpPtxAAAgAElEQVRDxYPqnOmx\nzgi8kpp9jB0SO7hDt+1/SpZdbStKjHOezWadVda6VfUzQW/W+gcAAAD3MHkCAAAAwCeQ2AEA\nAAD4BBI7AAAAAJ9AYgcAAADgE0jsAAAAAHwCiR0AAACAT2C5EwAAANhGh/cb9Q5hF0FiB7W7\naZq/yOZqO1cYZsaLHSN0276W0xPZnGJa2WwumdMPaKr7agEAwCvsLd3bCu3DeJ8vC4kd1C5h\nWYlcrYmdEGHFg9svY9tvZbPhZFJRlFwul8lm92vqLlpeHQAAIA/G2AEAAAD4BBI7AAAAAJ9A\nVywA+E0iyz9eF7WdyzkPhrwNB6ABrFk8w8xbWSKitCG4bX4Kg1b8CYkdAPiNYVJGr/FDi3Om\nBLwNB6D+mEmUtkm1iIhlbJvbREjs/AldsQAAAAA+gRY7AACARsd0ohWLiFi23qFAY6tbYjc1\nNbW4uEhEfX19k5OT1ZeJx+MnTpxwylQ4HQAAwB9s3RYf2/WOomksLy8TUU9PT0NVtTOXqE9X\n7Pz8/NWrV+fm5ubm5ohoamqq+jKxWKyvr29uA7I6AAAAcCwvL/f29jZaVTt2ifokdjMzM2Nj\nY/Lx2NiYbJarskwsFuvu7t6ZOAEAAACaSB0Su3g8TkT79++Xh/39/US0tLRUZZn33nvvnnvu\n2cF4AQAAoDk4DWC9vb1nz55dXl5mjJ09e5YxxtjticADAwNsQ/6JLI88t7iqhYWFgjLO4cLC\nglNb8SWKT19YWCi4hCe/gTqMsYvFYkTU1dVVW5nFxcW+vr6ZmRl5KDtqHb/+9a9/+MMfOofD\nw8NOdlhA0zQhalzpKp8QgnMeiUTcV0VE8g7QNI1zD3JuzjljrPrYVMsKmlbl2BRFyf8/oWby\ntg4Gg+6rIiL5pxRCBIPBSCRSHJ9tY2wK+Eo1w5QnJibeeecdInr66adHRkZ2ND6AIuyKwZYN\nl5XYPYrdWyl16enpuXLlSm9v75UrV3p6euTwtbffftv5FBgYGDhy5MiFCxeI6OzZswMDA/Jx\nb2/vuXPnhoaG5POnTp06efJkcVXf/OY3ZVWyzPe+9z3ncHh4WD4ud4mC02X5/Eu4/OVIjTIr\nNhaLyWa5ymVklnbs2DH5RhaPx0dHR/Nzu6tXr77yyivO4SOPPPLAAw+UrE3TPNiB3hEKebmk\nqaqqqurZDsfVxyYsS8tsMuFKCOFJQix5+1eQsYVCISR24G/OEGQimpiYmJqaGh8fLygzNTXV\n3d0t3ypHR0eJCLkd1FnCpmum20ruruUD6PHHH5cPFhYWLl686KRZJ0+ePHXq1MLCQm9vb/7H\nxGOPPXbq1CmZyRV4/vnn88sUHC4vL1+5cqXcJYpPL3kJlxolsSvXrlZQpqurKz+Nk016S0tL\nTlLY0tLy4IMPOgWCwaBhFH4/UBSFiCzLsqyyrVPVY4xxzk3T9c1KRNsQmxCi+DdQjmFZFX4Q\n2f5n23YD/t7yYzMMo2Ri52GuDFBfMzMzp0+flo/HxsbOnDlTkNjF4/HFxcXp6Wl5+PTTT58/\nfx6JHdRZO7Pvd511tNfSZeTMTrh8+TJtdEA5Ll++LBvqFhYWhoeHq6yq5GGFSzhdrjXEvyV1\nSOxkDhePxyv0xlZTpqSHHnro1VdfdQ5XV1dXVlYKyuzdu5eIUqlUJpPZUuUlBQKBUChUfJXa\n7Nmzh3OeTqfT6bT72jRNi0aj1ceWs6xkMlXu1Wg0yhjL5XLZrAfLKAkhwuFwMpl0XxURhcNh\nRVF0Xc9kMiu8dFex/LsDNLtyQ5DzOz0KvgMXy2azBf8jF3wOOYcF45BqJivxsKrixy4r9DY2\n739vzJsInWo9rK1K9v0KuU/sXDt69KjTnJZP/kKcXlc3GVjJS2xH41xJdfgVy1wtFos57W20\n8d60aZmlpaUzZ84UvGFV09oHAOAP1QxTLpDfwie9/PLL+aNWLly4EAiU3kmtvb29pjBLK3eV\n2rS1tXlYW2dnp4e1tbS0eFhbZ2enHbSsm96sTRwMBoMhLjpL/C10XffkEg3r0KFDFy9eXF5e\nLhjQtrCwkJ+NXblyxfNL7Jj6LHcyODg4OzsrH8/Ozg4ODlZZpr+/v6+vz5lCu7S01NfXt9VW\nPQAAn5HZXrGJiYnR0dG+vr5NBzED+IbMqEomZ0NDQ0ePHn3qqafkoZyjKtvSZDZGRMvLy06H\nbIWqyqlwia1GW5v6NIqOj49PTU3J8byDg4PO6JCJiYljx47JgSDlykxOTsonCdtOAAAQUfmO\nC/kOubS0VDDP7PHHH3/kkUecw3Q6XTA0RQgRjUaJKJFIeDKsVs7i8mSQCedctoetr697Mk43\nGAwKITwZGcIYa21tJaJUKuVJ61cgEFAUJZlMUspmSbdTSuUiCblcTrdMe7XEYCTbtr1to62X\n48ePDw8PHz9+/Nlnny146cKFC3ItEnko+157enqOHz/udL/mz1StUFU5JS9RIbdzLuGMi3WD\n+Xu24OrqavH/WnKs1fr6esOOsUsmkx6Osbt582aV5XOW9Q8Vx9hxzouH5tRGjrFLJBLuq6KN\nMXa5XC6TyXylJdr4Y+zW1tZyuVzBk52dnYyxev31K+vo6BBCpFKpVKrsHVI9VVVbW1tv3Ljh\nvioiam9vVxQlk8msr6/LZ26l+AdrNX5r5ZxHo9FEIuHJe6Mz+jOdTvfuyyll5vNt6eaU2ypO\nT087nRWjo6OnT5+u3CZXucyNGzcKfl5FUeQH/K1btzxJnmSa6PyN3BBCdHR0UJl3+BrIP9Pa\n2pr7qhhjsku35P/jNQiFQpqmra6uUsoWV91m2DLpzGQyWa5b95XusvP8rTKRSLC3PO7htQ+r\n3nZ2+0l9umIBAKA2zhBkeVhymLJsotv52ACg7pDYAQA0mU2HKZccjoxhdgC7ARI7AIAmMz4+\n3t3dPTo6Ojo62t3dnT9MeX5+Xj6enJycnZ2VZWZnZzEcGWCXqP+KMgAAsFXj4+PFu00UZG9I\n5gB2IbTYAQAAAPgEWuwA6kAIUW6lVkVRPFnEVW5P59V6sHLevlexye2GvY2Nc+5UGDC5qtb4\nrdX5ST2MjTGmqmogwErOivVkmjkAgITEDqAOVFWVyU0+mQSoqupJViF34w2Hw+6rIiLOOZUJ\nuwZyO6Ptiy1tUSDgarskb5NOIQTnPBzWkNgBwHZDYgdQB5lMptw6dt7uFHzr1i33VdHGOnbp\ndNrDdey8ik2uY5fNZp010lZTfH3d1Tp2yWTSw3XsDMNIp9O3bpVdxw4AwCtI7AAAAGAb2YfV\neoewiyCxAwAAgO2CLSJ2GGbFAgAAAPgEEjsAAAAAn0BiBwAAAOATSOwAAAAAfAKTJ4CI6GeZ\nzHXdqHcUAAAA4AoSOyAismyy6h0DAAAAuISuWAAAAACfQGIHAAAA4BNI7AAAAAB8AokdAAAA\ngE8gsQMAAADwCSR2AAAAAD6BxA4AAADAJ7COHQAAQOOyf5UTN02y6x0HNAkkdgAAAA3MJDLr\nHQM0D3TFAgAAAPgEEjsAAAAAn0BXLAA0Otum6wlR7tU0MSEom2Wp1O0yWZPtVGgAAI0FiR0A\nNDrG6GaqbGKXZSQE5XIskylbBgBgl/B5YqdpmqZp5V4SwoOPASEE5zwSibiviogYY0SkaRrn\nHvSSCyEYY9XEFiIW1PVqYlMURT5wiTHGGAsGg+6rIiL5pxRCBIPBSCRSHJ9tY0YZAAD4n88T\nuwrpEefckw97zjljzJM8zOFVhTIDq6YqmWZVWadXiZ3zX6/I2Djn6IcDAIDdyeeJXSaT0Ysa\nogKBgHwpk8m4v0QgEAiFQolEwn1VRLRnzx7GWDabTafT7mvTNC0ajVYTWyqdSRtG5TLRaJQx\nput6Npt1H5sQQgjhyY9JROFwWFEUwzAymUxCESUTO/l3BwAA8DHMigUAAADwCSR2AAAAAD6B\nxA4AAADAJ5DYAQAAAPgEEjsAAAAAn0BiBwAAAOATSOwAAAAAfAKJHQAAAIBPILGDO/5hPbmU\n8mDRZgAAAKgLn+884XumbV8vv2OEShTJZlc22wSWiLK2/V5On7mxojD6twf3h7ApF8BuUryj\ntLMVYTgc9mT3RVVViSgajbqvytmKMBQKebKjjNwC29vYgsFguZ3Kt0RRFCYMr7bVdurkAYVF\n1eKXTNP08EJQF0jsmptu088zZTf4UgwzRCxRvkC+hGURkWFT2rJCXHgWIgAAAOwUJHYAALtd\nMpksaJZTFEU2OKVSKU9acWR72Pr6uvuqhBCyoS6dThfvBl4Dudm0J7ExxpztyHO5nPsKQ6GQ\napInO5sTkfybGoaRtXRrvfR3/uLmW2guGGMH8AlTU1Ojo6Ojo6MTExO1lYnH46Ojo/F4fDvD\nBAAAKAGJHcAd8/PzV69enZubm5ubI6KpqakaynznO9/ZgVABAACKIbFrMrptr5qW808OjPPW\nbw39N7lc8b9fpTPL6cyvM1nnmQ/Lz9toUjMzM2NjY/Lx2NjY4uLiVsvMz89vd5AAAADlYIxd\no/vIMD7Oy5/Slv3xNs9amvzwRvWF/0176x+2tWxfMDtJdp7u379fHvb39xPR0tKSfFBNmXg8\nPjMzMz09feLEiZ2NHQAAgAiJXeNbMa3f6o3bMPbLTJb8ktjFYjEi6urqqrnMd77zndOnT5d8\n6erVq3/1V3/lHI6MjPT29pYsqWmaEB7MSuace7WCA20sfqFpmrMKhsvathpbMFj2ujIkRVE8\nWRJCLlfhySIaRCT/lEKIYDAYjWpKqT+sJ2P2AQAkJHZQaOLuztZSH97hUJhxrudyOT1HRP9p\nZe1f0lUtpFKBTfTvb66oxJ7c0+ayqm0Si8XyW+wqlJmfn+/u7u7v7y85beL69es/+MEPnMNH\nH330c5/7XMnaVFWVK355wvPlrxTFszeNLcW26YpgnHNPlg3buJxnVdFGbMEgIbEDgO2GxK5x\nmbZNRB4sDLpFn1bUPaU+f6KhIOc8y1mWERFFvVjr7n3d+LtEkoj+oDVyl3cZg4ecXtfKZWQn\nrJxOUVJbW9vDDz+cf1i8TIPM50zTtLwYOskYE0IYHo2DlCu4WpblycoXjDFFUba0UIVhlF00\nWwjBGLNt26u1VRVF8er3lh+brtu292NiAQA+oRE/SoGI0pZ9PpmsdxTbTt/4oNOtnc9gC8kc\nLh6PV+iNLVfmxz/+MRGNjo46z5w4ceL06dNOa9+hQ4e++93vOq+ura2trq4WVN7Z2ckYy2Qy\n6XTa7Q9DpGlaNBotvkptOjo6hBCZTCaVSrmvTVXV1tbWLcWWSpVtQotEIkIIXdc9WeuLcx6N\nRtPptCfbLcgF0gzDSKfTq6u5ki12AAAeQmIHcJvM1WKxmHywtLREG9MjNi3T398/MjIiy8Tj\n8RMnTkxPT1cergcAAOA5LHcCcMfg4ODs7Kx8PDs7Ozg4WFsZAACAukBiB3DH+Ph4d3e33FWi\nu7t7fHxcPj8xMeEsUFeuDAAAQN2hK3bb5YjWjGrHdBs5nXOe0o1V36392yzGx8eLc7XJyclN\nyzi6uroqzKIAAADYPkjstt0N3fh51WO6WxRFDp/3ZPfoHfCRYc6vJmo4kXG2J5v72PWCKQAA\nAOBAYgc14oyI6APD+I8ra7XW4c2ETQCARsZWbF7rjG0WMG0dg6ZgC5DYQY2ORcK/yeaytS4J\nccu0dC+WkwAAaHAsadNajW93tmaSUnYRR4BiSOygRp8NBl7Yf3fNp/8f8evv5vTPBLRfZpuj\n0xkAAKDxoYEXAAAAwCfq1mI3NTW1uLhIRH19fQVTDjctU825AAAAALtNfVrs5ufnr169Ojc3\nJ1eFmJqaqr5MNecCAAAA7EL1SexmZmbGxsbk47GxMdn8VmWZas4FAAAA2IXqkNjF43Ha2Eyd\nNvbilHtublqmmnMBAGC3Ye+Z4peW84/dxKR72KXqMMYuFovRxmbqWy2z6blvvfXWq6++6hz+\nyZ/8yX333Vdc7H//9bu/TmVsL5bbYIwxxizLKlfAJvuRaKQ3FKy+TlVVhRCexEZEoVComsKB\njV9GMBQKKSWuLmtTVZVzD74PyEqcqgLBYCig1Vy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gIkZkExr/fAuJHdyhcv5oOFTu1fbWFiFEOnt10uAAACAASURBVJ1OidvjVWK68Z6u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\nMpFIVC5mmhEiYRqGfKdKJpNqqQ6pSCQihMjlcplMxmVgRMQ5j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5Zl+b7fbDaHvwv1waxlqBZd2RRdQ4X5cVPPst7HraNCoXBwxu7u3btq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",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Aalen's additive regression considers the time-based changes in covariate effects\n",
    "# Can visualize how the covariates change over time\n",
    "# Results at the tail end of the dataset can get inaccurate (risk)\n",
    "aalen <- aareg(Surv(time, status) ~ treatment + age + sh+ size + index, data = prost)\n",
    "autoplot(aalen)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "22489d9d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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aJTJ9q0KSqlgCpUIHs/7oYN+Puzaxd792qzCfXLwrZvx9mZRo3kjyohTJqsin00\nk1sV+3Dp6WzahLc3Li5ERvLFF/znP3h55eu5j9zcIj8DtQ+XmsrMmVovya1bAEFBtGhBTAyr\nVuHmRtOmPE1uZup17B6id+/emzZtStEXPytkCQkcOMC+fRw5wttv07MniYm8+CLFivHCC7Rq\nhbe3+Yy1X7rEnj38+Sd//pm1pvjfbG1p2ZJOnejYkQYNimK2pC+MV7MmtrZcvap9rlxd6d6d\nXr3o1KkoxixE0VCUV8VqK7nEQ7zxxhvAtGnTjB2I4e3erXQ6BapNG7Vxo8rMzO8Tb9xQy5cr\nX19lb68gly9LS+Xjo2bNUuHhTx7euXMqKEilpyullL9/1skrVFD9+6uMjCc/s1nq1auXjY2N\nsaP4R1qa6tNHOTpqPzNbWxUUZOyYCkBkpFqxQr31lqpZM/dPwv237IABas0alZBg7Ijztm+f\nGjtW1amjxRwaqrVHRT3Gfw1CPBsCAwOBBQsWGDuQXJhsnSphCG3acPw4//d/hITQvXvOaXAP\n4eLCwIGsWcONG2zfznvv5exF0w/Ujh+Puzs1ajByJDt28LgLUqtXp0ULbRy2Rw9CQli0iEGD\ncHIiLEyb9fTbb9SrR9++LFzIgQOkpj7inMHBwcH357+LgmNlxS+/cOsWBw7w2Wf0769tORwS\nQuXKdOmCn1/u26GYlsqVGTCA774jIuL/OnceYmVF3765VL+7do2VK+nTh3Ll6NcPf3+M0rH6\ncC1bMns2p04REcGOHTRqBODnp60mfuMNfvqJ2FhjRymEeBRjZ5YmwIx77O67eVPNmKG+/Va7\n++ef6vLlxz7JiRNq1izl46P1Av77q3Rp5eurli9Xt28bLPKNG1WtWllXrFtXa797V508qdLS\nch7fqFGjRo0aGezyRUnR6rHLS1SU6tRJWVsrUBYWqkMHrUvW9GV9/zMz1ZEjavZs1aGDKl48\n9w9DqVLqzTfVli25vEeLlGvX1Jgxqn59LeyaNY0dkBBFQlHusZPFEwLA2ZmPPtJuJybSpQtp\nabzyCqNG0axZfk9yf0XtjRts2cLGjWzaREJC1gFPsKL2kbp1o1s3bfP30FDu79U5ZAg//4yd\nnVbG67XXtEn/UsfOyCpWZMsW7txh0ybWryc5mcxMLC3Zt4+9e+nUCU9P053alZ6ePnXq1MmT\nJ9O48a7bt2fv3Gnl7V3vzp3GsbFtExPL3riRdeidOyxdytKliXZ2dgMH8vU72SMAACAASURB\nVNpruzMyPp8zJ+OfTW9btmw5efJkYNeuXbNnzzZg+4ABAwbqV/7mR/nyzJnDnDlcvcq2bVn7\n6r7zDlu20LEj3brRrh0lSjzFt00IYVDGzixNwLPQY5fDzp2qfXutG6xjxyfvUklMVNu3q/fe\nUxUr5jn7qHp19d57avt2lZpqyJdw+rSaNk299JJydVWgOnfW2itWnFSmzPIff1RnzpjbxCHT\n6LHLy7Bh2huicmU1YsRTzc00kk8//dTJycnb21t/d/bs2U7ZeHt7q0uX1IIFV6pWzfWTkFS8\n+M82Nn3t7V3uH5/XeZ6i3dLSsl69egZ4tcuWZc3Gs7ZWX35pgHMKYTqKco+drIp9NDNbFZt/\nJ06wcCHHj7NjBw4OpKSQkqJtOvW4MjM5elTbo/bIkYJaUZuX6GhKlUK/ENbBYf+9e9rGF/b2\n6W5uX1aoEKC/W3B9JIZtz6vHxZirYp9eRgYhIWzcSEAAx48zYAArVgBER2NhgYuLseMzqPBw\n1qzhl184fTqXR8uU4ZVXGDAAHx+Dd14aYK/h7M6dY9Mm9uzhP//B15eMDIKDqVu3SOweKERB\nKsqrYmUoVuSpXj1towG9115jxw4GD2b0aK3mXP5ZWODpiacnU6Zw6RJbt7JhA9u3PzCDvCAG\navXuj88CL7/87bFjX3z44U9hYWzcGHnxYtjVq4fBKi4u7M8/ix88iJcXly/HHTx4DLTg7t27\np0+wjhw5cvDgwfunMkp7cnKylZVVXkNpGRkZ48ePf9zvT/ny5UeMGGFlZdT/DSwttSJ5n33G\njRuULg2QkkLVqqSl4eNDr1706vXY77yiyd2dKVOYMoWTJ1m7ltWriYjIevTWLZYsYckSKlXi\n5Zfx9TVghmfgOo41avDf//Lf/2p3T5/mhRewtaV3b95+mxdfNN1RdSFMmLG7DE3AMzgUm6vA\nQNWokVbKpE8fAyyASEhQ/v5qyBBVoUJhD9T+24wZqnVr5eCgXdfPTyml0tPV6tVq0yZ1/XrB\nXj3/kpKSkpOTc31o+FNs8LV3795CfiH5tXat6tVL2dkpUDqdKrJxPqUTJ9S4cXlOWXBzU++9\nl1V/5Ck85P1jGL/9pjp2VBYWClT9+iolpQCvJYTxyFCsaXtmh2JztWMHc+eybRsrVtC/v2HO\nmX2g9vDh3I8puIHaHJGcOUNEBK1bU7Ik589To4b2UOXKtGjBokVFd1QwIyPj0r83RXiUn376\naeLEiTt27GiXY6fRIiUxka1bOXGCYcNwcSEoiAkT8PKiVy98fEx4E7McMjMJDmbtWtasyb0W\njLs7vr707Uvt2oUe3OO4eJHvvyc+nv/9DwsLIiK4fJnWrc3nJyWeeUV5KFZ67B5Neuz+7cYN\n7ca2baphQzVrlrp1yzBnvnBB+fmp7t2VrW0Blj7Ov/BwtXixGjhQ1aunKlZUR48qpVRYmPLx\nUb6+6rPPVECAio4ujEj0goKCggxa6febb74BduzYYcBzFriDB1WVKtobwsVFTZhg7IAMLT1d\n7dun3ntPubjk/jFwd1eTJ6uIiMc9scHfP/nSrp22LGbyZBUZWdhXF6IAFOUeO0nsHk0Su4cI\nD9cGUkuUUMOGGfI/7Zs31fLl6tVXs4ZH//3VuLH6+GMVHFzYpdDCw1XjxsrKSgujeHEVE6OU\nUklJKjAwK+stCAavw2eSiZ1SKjNThYaqjz9W9eurFi20xqNH1S+/GLJMotGlp6vt29WAAVl7\nePw7w5s1S0VF5fN8xqnjGBWlPv1U6ZcDW1qqn38u7ACEMLSinNjJzhPiqdSty8WLrFxJnTp8\n8w2jRhnszM7ODBzI2rXExLB1KyNGULVqzmOOHmXGDFq0oHx5+vcvvML4dety5Ah37xIczBdf\nMGmSNjr85Ze0bEnZslStyquv8uOPhr90WlqalOID0Onw9GT6dI4fJyhIaxw/ntdeo2xZOnZk\n8WJu3zZqiIZgaUn79qxYQXQ0/v4MGJCzYlx4OOPHU7kyLVuycCHR0Q8/n3HePxUr8sknnDvH\nli0MH66tgLl7l1WruHChsIMRwtzJqljxtGxs6N+f/v05cEDLb9LSGD2aF17g5Zd5+qWWNjZ0\n7EjHjixaxIULbN/Ohg1s2/bA7mExMaxaxapVAO7u9OhB+/a0aWOAqz9E8eJ4e+PtndXy1ltY\nWBAaSmgov//OgQPaNMR161i3joYN8fKiSRMcHAowqmfaqlX89hvr1rF7N9u3c/Ys8+YZOyYD\nKVaMHj3o0QM/P3bsYOVK/vgj6zOQmUlQEEFBfPABzZvj60u/fkWu5oiFBZ060amTdnfvXvr3\nx8KCLl149106d8ZCOhqEMAD5IAmDad6cOnUAkpL44w9ee40aNZg925D9JtWqMWQIGzZw+TJL\nl+Lrm1UJ/77wcD7/nA4dqFaNoUP5448Hdr8oUE5OvP8+q1fz99/ExnLmjNZ+/DgrVzJmDG3a\nUKoUb76ptWdmkpxcSLE9E8qUYcgQNm/mxg0CAhgzBuDmTUqXpm5dJkzg4MHciyiakOLF6dGD\nNWuIjmb5crp3x9o661H9Js2jRlGpEj16sGIF8fHGi/WhunVj3To6d2bzZrp103aGEUI8NUns\nhOE5OhIervWVjBtHgwaGT1/KluWNN1izhthYQkOZNQsfn5x/8F+5wpIl9OpFyZJ4eTFlCocP\nF96v9VKlsgbNJk8mNpadO/nf/xg4EC8vrb1DBxwcaNiQt95i8WKuXn30aV1dXQ1ciswsOTrS\ntSsVKgCULs3rr3P7NrNm0awZVaty+bKx4zOEUqUYOJANG7h+Xcvwsq85TUlh40YGDaJsWS3D\nS0igSL1/dDp69SIggAsX+PRT7pdm3LuXTZv4pxy3EOKxGXuSnwmQxRNPLDVV/fijmjJFuxsa\nqrZvL8CNvC5cUF99pbp2zXPjdVDPPadGj1Y7dhSJAlsbNqh+/VTt2trubW+/rbWvWKHmzFG7\nd6u4uJxPMXgdMlNdPPG4MjJUYKAaO1a99pq2vOXIETV6tNqzx9iRGc6VK2rBAuXjo72fcnzZ\n2Slf35Rff02+e9fYgT5U7doKlKurmjhRXbhg7GiEyF1RXjwhdeweTerYGUrnzmzdirs7I0fS\nvz92dgV1oaQkdu8mIIBNm7h4MfdjHBzo0IGuXenShYoVCyqSfIqL46+/qFMHZ2eUomJFrYqZ\nhQXPPce339KyZUFd2s/Pb9iwYa1bty5btuxjPdHW1vajjz6qa5C9QYxiyRKGDgVwd+eddxg4\n8An3yyuCwsP55Rd++SVrNkB2lSszbBhvv81j/sQLSXQ0P/zA999z7hwWFuzezQsvGDsmIXKS\nOnamTXrsDOXKFfXBB6pkSQWqTBn199+FcdHz55Wfn/L1Vfb2D9vfYsgQ5e9fJLrxlFJ37qgt\nW9T06apXL+Xhofz9lVIqNlbVqaOqVUvo0uXGokXq4EHDXGvbtm3W2SdpPY4PP/zQMEEYy7Fj\nasQI5eSkQHXrZuxoCsCRI2rcOK3OSI4vGxv1+usqMNDYIeYhM1Pt2KE+/VRdvaqUUpcuqS++\nUGfOGDssITTSY2fapMfOsOLjWbaMtWuZPZvmzcnMJCamMPoO4uLYto1Nm9i8Oc+iEM7OdO5M\nt2507KjtVlp0pKUxcCC//RaTlqatdgwIoGtXUlLYsYMKFahfnyfN0B5bZGSkm5vbmDFj5syZ\nU0iXLDhJSQQE8NxzNGhARgbjx+PqyoABlClj7MgMJ9dNafVq1Trftu2Ec+di/9nXtWnTpp99\n9hnw559/zpo1Kz093fjtlSoxfDg63XEnp00VK+4rWzbVwuLfx7dp0+bjjz82+DdPiH8ryj12\nUu5EFDYHhwf2DV+0iNGj6dKFUaNo374ANw0vWRJfX3x9Ac6f13Yw27s3Z9mUH3/U6s8VWtmU\nfLK25qefqFevTXp66UWL9l67RqtWACEhdO8OYGNDvXp4erJoEba2xg3WpBQvzquvarfT0liz\nhshIxo/n5Zf5v/+jbVujBmcgHh54eDBp0lc9e9betu3FtLSshUYREdUjIr7V6X6ysfnB1jbC\n0jIxMVEppdPpTp8+ffDgwft//BuzPTBQ5+FxbsyYOqGhDWJjG1tb97W3z3F8fHz8vn37JLET\nQoZiH02GYgvUrVvqjTeUjY0C5eGh9u0r1KtHR6ulS5WvrzZAnOtX5cpq6FD1xx/q3r1CjS1X\nHh4eHh4e2VsyMtSuXWrmTPXqq8rNTTk4qEuXlFIqMFC1aqUGDVKLFqn9+1VioiHD0G9KO2bM\nGEOetIhISVFr1qgOHbSd7M1y+O/cOTV2rCpTJpcN+/r0UaGhxo4vb9euqTlz1KZN2l0/P7Vu\nnUpLU0r16tXLxsbGmLGJZ0lRHoqVcifCyEqXZulSLlxg3DiiolixolCvfr9sSkwMu3czdiwe\nHjmPuXwZPz9eeokyZejYkf/9j9OnCzXIh7OwoG1bxo9n7VouXuTuXapU0R66cIHly/nvf/H2\nxs0N/Y4DiYmcOCH18/JmY4OvL9u2cfYsW7dSsybAmjW8+SZbtpCZaez4DKF6dWbP5soVli3j\n+eez2jMyWLMGLy/at2fbNuPFl7fy5Rkzhi5dAFJSGDeO3r2pUoWPPmpbpUqjRo2MHZ8QxlcE\nRpiEgIoVmTWLqVOxsQG4fp0WLWjenFGjHvi9U3CsrGjThjZtmD2bixfZtImAAHbvJikp65iU\nFLZvZ/t2PviAatXo3JkuXXjxxZybPBWo+0XI9u3bt2rVKvXPcFXnzp179+6d/UgfHy5f5uZN\njh3j6FGKFdNm4H3yCf/7H1ZW1KlDw4b4+vLSS4UXvympVk3b/Aq4do2VK1m2jKpVeeMN3nsP\nJyejBmcIxYoxaBCDBhEaytdf8/PPWW/3nTvZuZNGjfjwQ3x9i8RchH+zteXMGZYv57vvmDnz\nPSur906eNHZMQhQBxu4yNAEyFFv4UlJU167a6FCLFmrLFuOEkZioAgLUu+/mvqxQ/2Vrqzp0\nUPPmqVOnCiOk+3Xs3n777ewf5LZt2+bzDJGR6vPP1auvai+qcWOtfelSNXCgmjNHbd+ubt58\nxEnMeSg2L5cvq6lTVZUqCpRZvvDr19WECapUqZxv8WrV1KJFKiHB2PHlLTNT7d6tvv5a6Us8\nRkYW0qdRPMOK8lCsJHaPJomdsRw7pgYPVsWKqZIlVXq6kYO5cEErm+LomGeS5+KifH3V8uUq\nNrbA48nMzIzNJi0tbfv27fPnz3+sk8TEqKQk7fbIkcrSMuu1jByptd+7p27dyvnEZzGx00tP\nVzt2qMhIpZS6cUMNGqRWrFAGLRltZMnJavlyrUpw9i8HB/Xee+rKFWPHl6es93/v3srCQr32\nmnnOjxRFgyR2pk0SO+OKjlZhYdrtWbPUxIkqKsqY8aSlqX371LhxytMzzwzP0lJ5eqpx49S+\nfQW400YOvXv3trW1fZoz3LunAgPVggVq0CC1cqXWqP8VX62a6tNHzZ6t/WZ/dhO77KKitP4t\nFxc1fry2aMU8ZGQof3/VrFku1e8GDFDh4caOLxdZ7/+zZ1WvXkqnU1ZW6u23zSrtFkVGUU7s\niuTMCSGyKVs2q8rd4cOsXcvnn+Pry6hRNG1qhHisrGjZUtsK4uJFtm1jxw62buXu3axjMjI4\nfJjDh/n8c1xcaNOG7t3p0aNg52XpP9JPc4YSJfDxwcfngcaZM/n1V8LC+P13bXPemTP1j4z/\n6aeaFy6sKF/+ir393VxOZ6Y6d+7cpk0bgIoVuXCBpUtZvJhZs1i7loiIAizYU5gsLOjRgx49\nCAzk888JCNB2WU5NZeVKVq2ia1c++ghvb2MHmiXr/V+jBuvWERLCxx/z3Xe88gqdOxs7OiEK\nkfFySpMhPXZFR0aG+uMP1batAqXTqf37jR3QP/LfjTd5sgoNLZBuvIIu95CYqP76SyubcuNG\nnE53PduruwKt//lPpRiYRXKTh4YNG+b81mRmqq1b1erV2t3ff1cbNqiMjIL7WRS2sDA1YICy\nssr5nvbxUf7+hdcp/VC5v//1G1copbZsUR99lHVXiKcjPXZCGIaFBT170rMnx46xYQPPPQcQ\nEcHOnbz6Ks7ORgvssbrxpk4tvG48AypenHr1tNsuLo5RUZkhIVHh4TanTtlGRTm9996qBg1S\nLl+26ty5srW1qlcvpX79lMaNU9q1S7S0NJ/tbTp37nx/R4QsOh0dO2bdnTGDw4epVYv33uON\nN7C3L8wIC0TDhqxYwYQJzJnDqlVZRb2DgujZk6ZNmTKFrl2NGmIeKlTQboSG8tlnzJ/P0KGM\nH0+5ckYNS4iCZOzM0gRIj10Rt3ixAlWsmBo0SIWEGDuabAq5G2/y5MnPP/+8gWJ/QikpaswY\n5eOjHBy0F6ivOH3rlpo2TS1dqk6cMP46mKfx7wLRuYiKUuPHq9KltU2Ri/CCgydx86aaPDmX\n4sbNmhm3C/3R7/8NG1SjRgqUnV0R6u0Xpqko99hJYvdoktgVcZmZKiBAdeyodDoFavp0YweU\nm6K2qLagZWaqiAgVFKTfFEDt2KH9dECVKKHatTPwThiFJl+JnV5CgvrmG9Wzp7pwQSmlkpLM\nahzwzh01c6YqX/6Bd7CVlRo+XMXEGDu4vGVkqJ9/Vq1bq927jR2KMG1FObGTnSeEydPp6NqV\nrVs5cYL//pe6dQGUYvNmbtwwdnD/qFqVIUNYs4Zbt9i3j3Hj8PTMeczNm6xdy6BBuLjg5cWU\nKRw+zNMthzAanY6aNWnRQitt264d587x669MmsSLLwLoxzNXrsTOjoYNeestFi8uWlt6PC07\nO4YO5Y8/qFoVYMIE3Nx4803+/tvIgRlEyZKMH8/Fi3zzTdZwZ3o6X31FrVosXKjtc1LUWFjw\n2mvs2YN++ct331G+PHPmkJho5MCEMCBjZ5YmQHrsTNHly8rSUtnaqn79VHCwsaPJQ3668cqW\nzW833hPUsTO6v/5S3burSpW0F1u6tDYeHRam5s9XW7eq6Ghjh/igx+ixy+HcOdWliwKtxNqN\nG4YOzXgSE9WsWTnfxJUrq+XLC3NdxZO8/48fV9WrK1AVKyo/P617WYh8KMo9dpLYPZokdibK\n319bPwuqS5cisnQvd/fuqT/+UMOGKTe3PDO8YsVUx45q/nx19Gju09Sevo6dEd28qbZvz5r4\nNGJE1guvUEFNmWLU4LJ58sRO7/Bh9fLLysJCzZ1ruKCKhqgoNWTIA0WuC3fi3RO+/1NT1Zdf\nqnLlFKg5cwogLmGeinJiJ0Oxwmz16MGuXZw8yfDhABkZALGxXLtm3LhyUaIEPXuyeDEXL3Lh\nAn5++Pri6PjAMcnJbNvG6NE0boyjIx06sHAhly5lHaD/SBdy5Ibi7Ez79jRvrt2dO5ft25k7\nl/79cXHhyhWtffBgKlema1cmTGDNGu7cMVa8T6pJE377jYsXGTkS4ORJBg/mzz+NHZYhVKyI\nnx8hIbRqldUYEoKPDwMHcv16QV//Cd//1tYMH87Zs3z9NT16AGRkPPC5EsLUSGInzJy7O19+\nyaZN2mSvV16hShV8fdmzx8iB5eX+bLyoKP74g2HDcHPLeUxiIjt2MGoU1avTtCmffEJwMOb0\nd5qtLe3b88EHrFzJsWN8+63W3qoVbm78+SezZvHaa/z3v1r7rl2sWcOZM2RmGivkx1G5svZ2\nvHGD5ctp04aWLdm82dhhGYKnJ3v34u9PtWpaS2YmK1dSsyZTppCcXKAXT01NrVev3q1bt4CD\nBw+6ubmV/keLFi3SHjLtz96ed96hdm2Ab76hWjX69uXChQKNVogCYj6/CYTIj7lz6dCB33+n\nbVvq1ycqytgB5c3ePqsb7+RJ5s6lXTtsbR84JjOT0FCmT8fHh82bl6en/7h0aZF+UU/pzTcJ\nDCQujuPHWbmSKVOy2l97jTp1cHTE25tduwowhoyMjNt5yHzcvLJtW06cYMAAQkK0vRzMQ48e\nnDzJrFk4OGgtCQlMncpzz7FiRQEtCOrfv3/79u3r1q1rY2MDODg41KtXz/Mftjk+OQ/Rpw89\ne/Lzz9StywcfPFCLUghToDPdsZtC8+abby5btmzatGkTJ040dizCMPQDL2vX4uen1VW9fds0\nCgUnJLB7N1u3sm3bw5ZXlit387nnLjz33MXq1a9069auYcOGQFBQkH5eCKDT6Tp16qRvNwPX\nr7NvH6GhhIZy6hSzZjFwIElJNG9OejpeXnh50bQpzZo97Y5fDRo0+Ouvv/J61MvL69ChQ09y\n3vPnWbiQpk3p3x/g4kXc3Mxhd7KrV5k6le++e6ArtXVr5s+ncWPjhZUP+/czYQJ//smUKUye\nbOxoRJETFBTUsmXLBQsWjNRPqyhKJLF7NEnszN7y5bz5Ju3bM3IkXbpgYSId2RcusG0bW7ey\naxdxcXkdlVS+/JkPP2zUqRNvv91i//799x949dVX165dGxISMmzYsA0bNlSqVKlQoi48GRkM\nGkRgYNaMqdWr6duXjAx+/x0XFxo1olSpxzvn77//vnXr1lwf2rZt29WrV1NSUp4uajh+nIYN\nadyYjz+md2+TeTs+xOHDjB7Nvn1ZLRYW9OvH7NmUL2+8sPIhKIjatXF25vZtgoPp2BFra2PH\nJIqEopzYyarYR5NVsWbv5k3VtauysFCgatVSW7YYO6DHpN/iYuJE5eWlvYpcvypXznj55Rtz\n557du/doaGhofHy8Uuqbb74BduzYYewXUYBiY9WuXWrZMq1kzIkTWd+TSpVUz57q1i0DXMVg\ne/VmZqqJE7XqIe7uavNmA5yzKPD3V9WqPfCOLFFCTZ6skpIK+sq7du16/fXX059mz5PvvlOg\natdW69YZLi5hwmRVrBBFmrMzAQFERDB2LLGx+PkZO6DHpN+pdto0Dh3i2jVWrKBv31x2zr18\n2eL3313GjKnRvn2jDz/0XLzYPu9BRbPi5ETbtgwapI22e3iwfz+LFjF4MC4uHD6sLdkMDsbD\ng06dGDeO1as5d85I4ep0TJvGpUt8+inR0XzwgZHiMDRjTLzT27Rp0+rVq6OeZvJp//58+ilX\nr9K7N61acf684aITwsAksRNCU706s2dz7Rpr1wIkJVGxIi+8wNq1/Hvb9yKrbFkGDGD1aq5f\n58ABJk/m+edzjualprJrFx9+SIMGTJjQH5bs3Vv29m0jRWwMzZszYgTff8+RI1y5grs7gLMz\n5cpx4ACzZ9OvH889R2wsQEwMK1eyf3/hbk9QqhSffMKlS+zeDaAU77/PwoWmvUdC8eKMG8fp\n0wwZkvWmvHyZQYN48UXCwowa3EPZ2vLJJ0REMGwYBw6wZImxAxIiT5LYCfEAa2ssLQGKF+f1\n1zl0iD59qFaNGTNMbHcvS0uaNWPKFEJCiI5m9WoGDcra/Om+27dLwP99+ml9Fxe8vZk0icBA\nU0pkDei559i1i9u3OXWKlStZupTSpQGWLWPgQFq0wNGR+vX55JNCjKlECcqWBUhPZ/NmRo2i\nWjVmzTLtpZr6incHDz5Q8W7PHjw9C6fi3ZMrV05bpj51KsC1a3z3HUlJxg5LiAdIYidEnubO\n5fJlPvsMnY6JE024jIizM337smwZV69y7pxWALlkyQeOycjgwAGmTaNVK60A8uefm/BmtU/M\nwoI6dejfn4EDtZaRI1m/nkmT6NKFO3fYtk1rnzcPd3d8fZk+nY0bSU21L8CwrK0JDWXePCwt\nmTCBhg1NPp8wasW7p+LqqpUd2r6d//s/6tThl1+euc+JKMqMPcnPBMjiCZGerhITtdszZqgm\nTdT//vfozVuLuIQEFRCgRo5Uderkud4CVPXqauhQ9dtv6vZtY0dcxKxZoxo3VtbW9ze6Pa1f\nPPHXX+rHH9WxYyo1tQCumpSkvvpKDRmibWx6966Kjy+AyxQi/VazDg4Ft9Xshg0b2rRpk2rw\nn0dGhvruO207slatVGSkgc8vijBZPCGEabO0pHhx7Xa1aly5wvvvU6kSb71FZKRRI3sKdnZ0\n7cqCBZw6xY0brFnDkCG4uuY87Px5/Px45RWcnKhRg5Ej2bGjSPenFBpfX44c4e5dDhzg66/x\n8Fiubx81iv79adgQe3s8PbUpmwZTrBjvvoufn7Z3Rbt2VK7MpEncumXQyxSigp9417179927\nd1sbvFKJhQVvvcXffzN2LCEhrFxp4PML8UQksRPi8fTty+XLrF5Nkyb88APff2/sgJ5OSEhI\n48aNU1Ku+Pri58fFiwQFMWkSzZppcw2zO3+eL76gQwcqVOCVV/Dzk9WBFCtGs2a88w5lypzS\nt6xaxY8/MmYML7zAtWscPaod2bUrNWvyn/8wdy67d/OQDa4ew+efU6UK06ZRtSoffmgiW6rl\n5v7Eu5YtsxpNYuKdo6O26mrcOICLF1mx4hmdpiqKBknshHhsNjb07cu+fURHa7tanThBixa8\n/z6nThk5tscVFhYWFhZ25swZ/V0rK1q0YOpUDhzgxg1++YXBg/l36eI7d/j9d4YNo0YNatVi\n+HDWrzftCf0GVK4c/foxZw7bt3P1Kp99prXXr4+lJWvXMnYsL77IjBla+/r1rF//pBuTtm1L\nWBh//IGHB3PmEBJikJdgNJ6e7NuHvz9Vq2othph4t3v37n79+mVkZBgqzFyULq39JfTLLwwa\nhKcnhw8X4OWEyJskdkI8ubJltW2fnJyIj2f+fNzdadWK9euNHZkhlC5Nnz58/z2XL3PiBPPm\n0alT1pD0ffr92Xr3pkwZWrVi2jRCQijQ36Em6vPPOXOGuDiCg1m2jMGDARIT6dOH3r2pXl2r\nt/fYxQV1Onr25MABzp/H2xtgwwZGjDBeIb6n1qMH4eF5Vrx7fAaoY5d/I0cyaRKnTtG8OR9/\nLF13ovBJYieEAbi68tdfBAXxxhscOcLQocYOyNA8PHj/fbZs4dYttmzh/fepVy/nMenpBAYy\naRLNm+Pigq8v337LxYtGiLYos7fH25tBg6hSBcDOjr//5uefGT+egVg3HAAAIABJREFU5s2J\njubGDYCLF6lShYYNGTiQefP48898jLLeX1564gRffUWdOgwebKqD5Q+ZeKfvpCyyihVj6lQO\nHaJ+fT77LGsRtRCFRRI7IQymRQuWLuX6dcLDtZYRI3jpJTZuLLpzn3Q63f1/86N4cTp1Yt48\n/vqLmBhtyYWbW87Dbt/m118ZMoRq1ahQgT59WLKEa9cMG7uZqFqV115j5kw2byY8nHbtAJyd\nefFF0tNZvZoxY2jTBv02v7GxLFzIr79y9mzeFTYmTGDHDlq1YulS6tQhj81tTYDpTrxr2JCQ\nELZupX17gPT0ovtfgDA7ktgJYWAODpQpo93W6di8mR49qFmTzz8viotJ27Vr17dvX09Pz+Tk\n5Nv/SMpWIy2v9oyMjDJl0C+5OH+ew4eZOZO2bbUKX9ldv87atQwdipsbrVszYwYHD8pY7SPY\n27NsGSdPEh/PwYNs2EDTpgCHDjFqFL6+1KpFyZK0b5/HVhTt2rFrF0FB9O9PqVIAmZlERxfm\nSzCYgpl4V+CsrenYERsbgLZt8fDg4EFjxySeCZLYCVGAFi3i4kWmTCElhfHj2bLF2AH9S40a\nNVavXn3t2jUXF5fS/yhTpsyhQ4eA06dP59VepkyZZcuW6U9iYUGTJowfz65d3LpFQAAjR1K3\nbs5rpaWxdy8TJ9KsGWXLZiWF4iGKF6dpU7p31zKETp04coQlSxg+nAYNSEzUJnEtW0axYnh4\n8PrrzJ79z8T9Fi344QeaNQNYsoQKFeje3VQn9ec18a527UdOvGvdunWbNm0q/HvflUIzaBAX\nL+Ljw8SJpKYaLQzxbLAydgBCmLmKFZk8mY8/5uxZatUC2LKFL7+kWzdefz3n9g/G4urqOmTI\nkHv37unvFi9evHr16g9pL1asWFxc3MmTJ/99qhIl6NqVrl0Brlxh2za2bWPnTmJiHjgsNpZf\nf+XXXwFq1KBDBzp0oG1bnJwK7EWai8aNadw4Z2OzZnTsSFgYP/3ETz9RsiSxsVhYcOwY69ZR\nty4Nm7xe67VAyzU/sXkzb7/NrFmm973WT7wbMICpU/nuO21wMzKSQYNYupT582nUKNfnde/e\nvXv37mFhYW3btr1z546+0cXF5cCBA/r3c4F7+218fBg8mBkz2LuXPXty7t8shOFIYidEYbCy\nok4d7balJYGBBAQwdix9+vDBB3h4GDU4cHBwmDdvXv7bLfL3a6lSJQYPZvBgMjM5coRt29i+\nneDgnH0W585x7hzffIOlJV5eWpLn7Y3BC8qasbp18fcHiI3l6FFKldIyh19+YeZM/SGOdnY/\nvvnaF1/GD2LJEkqXTpo0899rnE2AfuJdv36MHs2RI1rjnj08/zzvvMOnn+b111LZsmV79ux5\nfzqBvb29k5NTSEjIsGHDNmzYUOnfRX0Mq25dAgNZtIiwMPI9pVWIJyCJnRCFrUMHoqJYtYrF\ni1m6lKtXi+IQrWFZWODlhZcXH31E+v+zd99RUV1bAId/FCki9gJ2bBgxgoqigBXsGivGhiUa\nbEk0iS2JL2g0SqrYxdiNRsEuokYQC8WGYkNRrMQauygq5bw/5gYUESkzzADnW6635l7O3LsZ\nyWN77jl7J3LyJIGBBAayf/8bdXqTkjh8mMOHmT4dQ0NsbencmS5dqF9fTnBkVsmSyvYLlenT\ncXMjMpKTJzl1isIVS/LzdsLC+v/ecF0RqlcTdlaP7VoW79WLWrW0F3Q2NG/OsWNs2MCECcrW\n64QE5sxh/Xrmz6dnz7ffUb58+ZUrV6Y5mVLHUeOJHWBgwNixyuu4OKZMoU8f7O01fl+pgJGJ\nnSRpgZkZHh54eHDiBBYWAAkJDBlCmTKMGIG1tbbjex8jIyPA+O2NEplgaEjDhjRsyMSJxMVx\n6JCS5KVZ+pWYSEQEERFMnUrp0rRqhasrbdumLqCXMkNfP71Ht46OAx4Tn0zkgad+McX99nBs\nX9ymv4uAsmPD1hZbWz74QOlbpqP09HBzo317ZszA21vZRXHnDr16MWQIv/+u7BrRTY8fM28e\ns2czbhyenpiYaDsgKf/Q5f9qJSn/S/mNm5TEuXOsWcPs2bi48PnnfPSRViPLkIWFxaZNm5o0\naZLD6xQpgqurUhHi1i327MHfX9mB8bp79/DzU5quVqumvMXVVRcXiT18+FDbIbxHiRIlgA4d\n6NABnvB4zNgzq45/sP8i4/ozderSpWYhIcpIY2N+/ZXPPgN49Ag9PV1ZEvoGc3NmzsTDg7Fj\nlafRwPLl/P03Pj506qTV4N6tQgWOHGHIELy82LaNdev48ENtxyTlEzKxkySdYGJCRAQhISxc\nyIYNBAZy/TqVKmk7rHfr3r27ei9oacnAgQwcSHIyJ04o03ghIWnLWVy+zOLFLF6MgQF2dkqG\n17y5smlUi/T19V+9elWyZEktx/E+PXr02Lhxo3JQtGix5d5OYyIZO5bffqNCheDgL8+d4+RJ\nIiOJjqZ6dYDERCpVIi4OKyvs7LCzw8NDmWnWFVZWbN2Kvz/Dh3PzJsCNG3TujJsb8+dTpsy7\n3pfVOo7qVK8ehw/z009Mm8bs2SxZooUYpPxIT7yzxqWkGDJkyIoVK6ZNmzZ58mRtxyIVCHfv\ncv26svZm9Wr278fdnRYttB3Wm27cuGFhYWGg6o+pMfHxhIYqSd6JE+8s8mpmRtOmSpLXoIF2\n1qaHhISsXr1aCzfOCj8/v/Lly585cyadr+3fj60txYuTnExiYppMWTUFFhXF+fO8esWCBYwc\nSXw8n3+OiQl2dtSvz4cfaj+95t9/GTVK2W6tUqYMv/7KwIHpDr906dL//ve/hQsXFtPibOTN\nmxQvTuHCCMGrV+mUgpR0T2hoqLOzs7e395gxY7Qdy1uE9D6DBw8Gpk2bpu1ApILoxx+Fvr4A\nYWMj5s0TT55oOyAhhBAPHz40MjLy8vLKzZvevSt8fYWHh6hSRcA7/1hYCDc34eMjbtzIzejy\nBhsbGxsbm/cMGj5clC4t1q5N94sJCSI2Vnl9756oXDn1kzcxEWFhQgiRlCQOHxYxMSI5WY2x\nZ8WKFaJ48Td+LNzdxb17Woom0yZMEObmYssWbcchvV9ISAjg7e2t7UDSIXeaSZJO+/ZboqP5\n+mtu3eKzz/Dy0nZAADx58uTVq1f30tSm0zBV/1kfH65e5dIlfHxwc0tnfXxKo4sKFahenTFj\nCAzU3fYEuqhfP/T16dePrl2Vx5qvMTQkZf9oqVJcu0ZMDFu2MGMGHh5KA9ywMBwcqFGDYsVo\n1ozx43O9KO+gQURHv7E3VtWp4q+/cjeOLOrZE2Njunfnhx/e3TBOkt5DrrGTJF1Xowa//sq0\naUqTTODWLSZPxs6OAQN0cQNBLqhWTdlWnJREZKTyrPbAgbQJxOXLzJnDnDmYmuLkpDyrlcVT\n3qN5c86e5Ysv+OsvQkI4c4YMezZUr0716nTtmnqmSRNWrODIEU6e5ORJIiIYNQorK0JDmTCB\nKlWUhXoNG6Y231O/smXZsIGlS/n6ax4/Bnj0iP79CQnhl18oXFg1SlXHbujQoUZGRvr6+p07\nd7awsABOnDiharIC5N75xo3PrlxZbtSo0p6el7ZvDx4+PDPXiY2N7dKli3aWCUq6SdtThnmA\nfBQr6ZroaFG6tABhairc3cWhQ7kdwLVr14Bx48bl9o0zdO+eWL9efPqpsLLK6Flt5cpi6FCx\nbp34919tR5zrMvUoNsXWrcLNTdy/n5M7JieL+Hjl9ZEjwtZWFCqk/EUULiyePRNCiNu3xcqV\nIixMPH2ak1u9w/XrolOnN34CrK3F0aOqL65fv/71X4gjRoxQna9Ro4a2zpvAH3AdTDJ9nfDw\ncA18cFJGdPlRrJyxk6S8p1YtYmPZvJk//uDPP9m+nQcPcnXHQE7q2GlOqVL07k3v3gAxMQQG\nsmcPwcGkqUBy/TpLl7J0Kfr61KuHiwsuLjRvjpmZVqLWYR99lFp054svqFSJL7/Mamk7Pb3U\nGm2NGhEZyatXnDnDyZOAMnG2cCFTpwLo61O9Om5u/Pijmr4FoFIl/P3x82PECB48AIiOxsGB\nzz7jl1969ux54MCBly9fqsba/1cuePfu3Zdfa2Oc++ejYbvq/KNHFC/+rvGfffbZ2LFjnz17\nlq2PRsqfZGInSXmSiQl9+9K3L5cu8fSpktXNnMnNmwwerDyx1ZyUOnYvXrxI6dFkYmJi+l+P\nKq2fL1WKQYNMRowwTUri2DF27UoMDOTIEcPXn9UmJxMZSWQkv/2GkRGNGiW3aaPv4oKDA0lJ\n77y+SQGsJSsEx44xdy7r17NsGfXq5eRiRkY0aECDBqlnxo/Hzk55bhsZybFjyvnJk1m6lLp1\nsbPD1pZWrahQIbt3dXOjSRMGDSI4GCA5mTlzCA42+PPPZs2avT28WrVq6baRze3zu3bRsSOT\nJlWbNi3d8QXxp1F6L21PGeYB8lGslFe4uyvPmurXFwsWiBcvNHu7U6dOmb02zVW4cOHIyEjd\nPm8IDQsVmuzg8CTlgeDbfwwMkvX1j4MXuIJRmuv0799fsx+rJmXtUezr4uPFpEnC0FAUKiRm\nz1Z3XOnbuFHY2wszM+XvxdlZOR8UJObMEXv2iFu3snjF5GTh7S2Mjd/YyuvlJZKS1B27mty/\nLxo0ECDatk136YCPjw8QFBSU+6EVcPJRrCRJuWHVKsaNU57PjhqFmdm7qneph6Wl5SeffJLy\nGMvY2Lh8+fJ54fzj//3vRVKS+ZYtT+fMibp+vdazZ2/sQElK0oP6UB8mmpg8rVDhYlBQNXNz\nLC0tzczMIiMj1f5J5gEmJsycSa9efPIJCxbwxRe5cM8ePejRAyG4coVz57CyUs7PmEFQkPK6\nZEl++IHRowESE0lOzrCWnp4eY8bg6Ii7O9HRAC9eMGkSkZH88QdFimjyu8mWkiUJCWH0aJYv\np149QkNTPwUAXFxc+vbt21DTU/RSniILFL+fLFAs5Tnx8Zw4QYMGmJhw7BjTp9O+PX376mRL\nKB0QHa3sqw0OVjZQpsvKikePNpqZHYqI+KVs2VyMT33q1q0LpF+gOJOEICEBIyMSEwkOplmz\n3O9zqvrxVj23PXuWgQPx8ACoWZNr16hTR+l127fvu7fzPn/OuHEsWpRaVcTaGl/fHD5l1iBf\nXyZPZvlynJy0HYoEul2gWM7YSVI+ZGqKo6PyOiGBkBC2buXrr+nZkzFjNL4CL8+xtsbamtGj\nSUri6FElyQsPT1s85coVoOfDhz0tLPjwQ1q3xsWFFi0wN9dO2Nqhp6fMiUVE0LYttWuzdGnq\nT1uuUP14v33PiRPZupWzZ1m9mlWrePyYqVMRggkTSEzE1pYPP8TGBhMTKFyYBQvo3JlPPuHO\nHYDoaJo0Yc4chg3Lze8ls1K2BQHHj1OyJFWrajMeSYfJak6SlM81bUpsLKtW0bgxf/7Jp59q\nOyAdZmBAkyZMnsy+fTx4wM6dfP01trZpdxwLwalTeHvTpQslS+LsjKcn+/fnehle7WrcmJkz\nuXqVZs2YOJGEBG0HxLBhbN/O5cs8ecKpU3zzDcDLl/z1F97eDBmCvT3m5mzbpoyPrt7xdtBZ\n2rdXjuPj+fRTunVLu49a13TrRr16rFkDHD58uH79+v/884+2Y5J0iJyxk6T8z9QUd3fc3YmN\nVWrzCkH//iQm4uGBi4t2mqvqODMz2rdXfunfvUtQkGomT1y//saHlZhIaCihofzwA4UL06yZ\nUj/Fzi6/l0HW02PSJLp1Y+BAfv4ZMzO+/17bMSmKFOHDD5XXJiZcu0Z0NKdPc/IkN29ibQ1w\n8SK1awOlypTZaVPjnw8vb52e/G1RnrB1K/Xrs24dTZpo7zvI0JIlDBzIgAHs3XvGzi4yMjI6\nOrpiSj8QqcCTiZ0kFSCVKikvVJncpk34+VGjBoMHM26cbD7+TmXLKsVlQO/OHQ4cIDCQkBCi\not4Y9vw5u3ezezeAmRlNmxaAXhe1axMWxpIlODtrO5R3MjCgTh3q1OHjj1NPVq/On38SEcHJ\nk5w4UTHMYFT/kjsd7u04i83waz7lnG7XcT1Sd0ijhvZ6b9YG1gFt23LyJIMHs2yZa0oCK0n/\nkYmdJBVQa9fi5cUff7B8OZMn4+REy5bajknnhYWFAW5ujm5uAOfPExxMcDD79vHvv2+MfPZM\nWasHVK6MiwutW9O6NeXL537UGmZoyIgRyuuFC9m7F2/vHFScyyX6+vTvT//+ymF8vJ5p3HIG\nDjTeFZNAoR3JHTb9bczf6Otz5QqVK3PvHjt2YGWFra0ObEIqV46AABYvvhoSwunTp0+fdnFx\nAUJCQv7888+UPZHt27fv3r17Buel/EnL5VbyAlnHTsrfEhNFbKxSyWvNGvHhh+Kbb0RMjLbD\n0kl2dnZ2dnZvn09OFqdOCW9v0bmzMDfPqKGZtbUYOVL4+oq7d3M//BzUscukn34SIEqVEps2\nafAumpOcLLy8hIFBAoan+HA1A+aXnJwQelgI8ccfqX+JVlZi8GCRnKztaIX4+++/9fX1Bzdq\nJLy8xLNnn765hLZly5aqYe86L2WbLtexk4nd+8nETio4Dh4UtWoJEHp6wsVF7N+v7YB0TCYT\no0uXhI+PcHMTxYpllORVqybc3YWPj4iNzYXYhciFxE4IsWGD0sl45EjN3khz9u0T5cun/j0Z\nGwtv78REsWuX+PlnMXiwsLcXTk7i5UshhJgzR5iYiHr1hLu7+PVXceJEbgf79OnTpDlzBIh6\n9ZIvXHjwmoSEBNWY5OTkNOf/+eefxMTE3I41H5GJXd4mEzupQElOFvv2iQEDhImJcHPTdjQ6\nJquJ0bNnYvduMWGCsLcXBgYZ9LoQjRqJCRPEzp0iLk5z4edKYieEuHVLdOokChUS9+5p/F4a\ncveuaNfujb+kbt3Ew4dvDzx8WHTsKKpWFXp6AkSVKsr5wEAxZoxYvFgcOSKeP9dwtKqOGoUK\niSJFxPr17x3+8OFDIyMjLy8vDYeVn+lyYpdfF/RKkpRNenq0aMHq1Tx8iK8vwLNnVK2KoyM+\nPjx6pO348pTChWnblp9+4uhRnjxhzx48PXF1pVChN4ap6uf9/DMdOlC0KDY2DB+On1+e/bQt\nLPD35+5dSpUCuHpVF4qhZE2ZMuzciZcXBgbKmS1bsLPj8OE0Axs3ZscOrlzh8WMOH+bvv5Xz\n27YxezYeHjRujLl5anW8p0+JjiYpSa3RqjpqbNuGkRF9+xIbm/HwJ0+evHr16t69e2oNQtIV\nMrGTJCl9KQ0FzMzo0oXTpxkxAktL3N158UKrkWlPhQoVKmR3W0Dhwri6MmUKe/bw4AF79jBx\nIg0bpq01k5xMVBSLF9O7N6VLY2/PpEkEBhIfr4b4c1Xx4gB37lCtGo6OSguvPERPj4kTCQxM\n7V9x7RotWjB7drrDzc1p3JhatZRDb28uX2b7dry8GDAgtSp4587Urk3Rojg4MHw4hw6pL+D2\n7YmIYO7cdzfckAqEPLkrNiYmpsZrG9BjYmJ27NgRFRUFjB8/vobO7U2XpDxv7lxmzGDdOpYs\nYft2bt1SWla+eJH7DaW0aevWrXrqKPpXpIhSCQX491/27SMkhNBQIiLeGJaUREQEERH89BOG\nhtjaKu9q1iz7tWliY2N7p/QwyBX9ra0/ioh4VbfuClvboGrVNHejli1bjho1Su0X5eRJ3N2V\nMjYvXzJ2LPv3s2yZkrm+g54eVlZYWdG58xvnvbzYtInTp4mK4sgRQKmXN2IEly9jZ0e9etSr\nx4cfZqu6ZNWqqD6Bp0+ZOJFhw2jQIOtXkfI4bT8LzpqAgICUyB0dHYUQFy9eTPMdeXh4qPem\nco2dJKVr3DhhaCi6dhX+/qLgrMPet29fnTp1qv3Hycnp6dOnQog9e/bMmjUrhxe/dUv4+goP\nD1GlSka7LgoXFq6uwtNT7NkjXr3KwvX79OmTm79fUrSAKyBAoyWMTU1Nc/j5v9N/u2VT/w6q\nVBGHDuXwqq+vpxwwQBgbp14+5RfOli1iwwZx/rz4byNE5ly/LkxMhKmpWLHi7S/eunUL+O67\n73IQe0Gny2vs8lJil5LDOTo6Ojo6Ah4eHqoXAQEBFy9eTEn7AgIC1HhfmdhJUrqOHxdduwpD\nQwGiYsXMLNrODw4dOuTg4NDwP+3atXv+/LkQonv37sbGxmq8kWprrbu7qFAhoySvSBHh6iq8\nvMSxY0rNGh31+LH44guxdq2GLt+tWzcjIyMNXVzh7y9KlUr96E1MxMqVarx8YqK4cEFs3ix+\n/11ERwshxPPnqdmesbGoX18cP57py504IaysBIhx497+h9emTZtu3rypxuALGpnYqYeHh8fr\nn6O3t/fbaZwqt1NN5qmLTOwkKQM3b4oZM4SdnfjlF+XMpUviyROtxqQNGk0sUuqnlCiRUZJX\nurTo3FlJ8nShyto7hYcLT0/1bgDOjcROCHH9unB0fOND/+KLLE6mZU1UlPjjDzF2rGjTRtSu\nLXbtUqIwNxflyonWrcXo0WLZsndM3N69K5o3F6DeBFQSMrFTF1Ual/GZd53MCZnYSVLmxcYq\n00hDh4rwcG1Hk4tyJ7FITBTHjgkvL9G5syhaNKMkr1w54eYmfHzEpUuaDirrfvhBgKhVSxw9\nqq5L5lJiJ4RISBATJwp9/dTPumXLXK43/fKl+Oor4eyc+jMQGCiEELdvi08+ERMmiLVrxdmz\nIjFRiJcvxR9/iH/+SXMFWccuh3Q5scuTmyckSdJZFSsybx5LlrB0KUuX0qABBw5gZqbtsPIL\nAwMaNqRhQyZOJDGRkyeVxmUHD/Ly5Rsj79zBzw8/PwBLS5ydcXWlfXsqV9ZK4G/67juMjfn+\nexwdmTaNiRO1HVBWGBri5UWrVvTrx4MHAPv2YWfHhg00bZo7IRgZ8dtvAEJw+TL37tGoEcCN\nG6xbx/PnyrBixTh92qjSsGEJCRwNwyJgmVXbmnrNmz169KhatWpff/31sGHDChcubGFhoRr/\n8OHDhw8fql7n5nlJzbSdWWZBynI61WHKirqLFy+mjFGtw5OPYiVJ6yIjxdix4uOPleqsV6+K\n3buVYv35kqenZ+PGjbV19wcPxObN4vPPhY1NRtN4+vrCzk58+aXYvl08fqytYP9z8qSoV0+A\niIrK+cVyb8YuRUyM+PDDNxpULF6cqwGk59Urcfas8PUVnp7iq6/Es2dCCLFypRKjGXH2Ve4O\nH/709TRg06ZNQojY2FhDQ8PcP59HyRk79ejdu3dYWFjHjh1VKV3Hjh0dHR3DwsIGDRoUGhqq\nGjNo0CDVSG0GKkkS2Noya1bq4bffsnYtZcowcCAeHqnlvvKNKVOmTJkyRVt3L1GCbt3o1g3g\nzh2Cg9m7l717uXTpjWHJyURGEhnJrFnK5F+rVrRqhbOzNmZV69XjyBHCwrC2zvV7q0P16oSF\n8cknyrzoy5d4eHDsGHPnYmSkraAKFaJOHerUwc0t9WSvXsTHc3L/o6itF89cq3Ztpfj9p3l3\nHsRGRdUPD3eZN888PJwPPij/1Vdz9fSuqt5iZGSkmkyxtLScPn16ykybes8fPnx4xIgR27dv\nr1ixosY/moJD25ll1qh+PlIEBASkbKFI+ZJ6p+uEnLGTJHW4eVN8/72oXFlpRPvTT9oOqGC4\nelUsXy7c3d/offr2n0KFhJOTmDxZBAVpvv9Vul68EJUqiZ49s92FTAszdipvV0JxchI6u+H0\n9m3h5CRAzJghhNi7VzRtKooUUQIvX14ZdeyY8PQUvr4iOlqzW60XLVoEBKpWCOYpujxjl8c6\nT4SGhl68eNHDw8Pb2/vixYsdOnQYM2aMKrcLCwsDPDw8UmbvJEnSHZaWTJ3KlSvs3cuXXyqL\nkV6+ZOFCgoJITtZ2fDkWGBiY8u9M3VGlCoMHs2oVN25w/jwLFvDxx7y9tCkhgdBQpk/HxYUS\nJWjeHE9PgoNzscWIsTHNmrFxI/XqERiYW3dVB1WDig0bMDdXzoSG4uSko502ypUjKIjp02nd\nGmjVirAwHj/mwgV8fVm3Thm1ahVTp9K7N9bWFC3K6NHK+RcvuHVLS5FLmaftzDIPkDN2kqQh\nMTFKGbzKlcXkySImRtsB5YDa69hp1LlzYtEi0bfve2byTExEixbC01Ps2yfi4zUf1vLlomhR\noa8vZs/O6lu1NmOX4uxZUbNm6mdXooTYu1eb8WSGv78IC3v7dGKiOH5c/PmnmDRJdO0qpk5V\nzrdrJ0AULy6cnISHh9i/P6f3lzN2mpCX1thJkpTPVK9OTAyrVrFyJdOn88sv/Ptv6sRH3qL6\nv1RtR5FZtWtTuzbDhwNcuMD+/Rw4QHAwN268MezFC/bvZ/9+pk7FxISmTWnZklataNw4+z3N\nMjJ4MK1a4eHBWy2F8oA6dThyhP79UW3se/iQdu1YtIhPPtF2ZO82fTpHjzJzJuPGvd7CzMCA\n+vWpXz/tcE9PbGw4eZLISEJDiYujeXOAr77izBkaNKBmTWrVokkTChXK1P1VDfrU0qZPSlHQ\nE7vExMS9e/c+fvw4gzFXr14FkvPBsyJJ0j1VqvC//zF5MiEh3L+vZHVr17JvH25uuLign8cW\njOQ9tWpRqxaffgpw+zYHDxIYSEgIUVFvDHvxguBggoPx9MTAADs7XF1xcqJ5c4oVU180Vaoo\nXVmBu3c5eJDu3fPMD0Hx4vj7M3UqU6cCJCQwdCiHDzN/PoY6+dt240a6d2fCBPbv588/M+5+\nCzRtmlrR5dYtypZVXj99yqFD7NmjHE6YwE8/AQQEEBeHtTW1a6f/LwEXF5e+ffs2bNhQHd+M\n9B/tThhqQpa+r4MHD2byg/r00081GrYkSSk8PZX6rxUrim++EbduaTugTND+o0B1O39e+PiI\nvn2FpeX7G9f+8IM4cEC8eKHWCH77TYBo0UJcv/7esbr1+S9ZIgoVSv2M2rYVjx5pO6Z3iIsT\nvXoJEB99lMMrXb0q/P3F77+LM2eEECIxMbV+sqGhsLFJfTQqy/BeAAAgAElEQVQdH5/nu0vL\nR7G6q0mTJgcOHHiZprLnm3799dfdu3fLzdiSlGumTGHoUFatYtUqZs4kORkvL23H9D62trY3\nb97UdhTqZG2NtTUeHgDnz7Nvn/Lnzp03hj1/rhRJBkxNcXCgRQtatKBJE0xNcxbBiBFcuMDi\nxdjasmgReaiO1dChVK1Kr148egTw9984O+PvT5Uq2o7sLWZm+Poyf37O10BUqUKVKnTqpBwa\nGBAVRXg4J09y9iy3bil7ce7fp0IF9PWpU4d69bCxYfhwihTJ4c2lVHoi7ywK0ZYhQ4asWLFi\n2rRpkydP1nYsklTgREdTuTKmply9Svfu1K7NoEG0aYOBgbYjK6hu3iQ0lMBA9uzhypV3DjMw\nwNpa6XjRujWlSmX3fgEBDB3K7duEhWXQ2qF79+4BAQEZ/ys9t8XE0KkTFy4ohxYWbN1K48Za\njel9zp/n1CmN5tBCMGUKhw4RHc316wjBH3/cHzas1L17jByJmRk2NtjYYGtLhQqaiyKnQkND\nnZ2dvb29x4wZo+1Y0sojCxckSSqorK2ViZ/ixbG0xM+PDh2oUkVZxSTlvvLlcXPDx4dLlzhz\nhnnz6N2bcuXSDktKIiqKxYvp3RtLS5yc+OYbdu7k6dP0LpqBjh05fZpffqFOHTV9B7mlRg3C\nwmjRQjm8fZsWLVi7Vqsxvc/y5Xz8MR9/zLNnGrqDnh5Tp7J7N1ev4u29DGpZWUUCz55x+DAr\nVzJhAp06UaUKp04BPH/OmjUEBSn926T3komdJEl5Q/HiBARw9SozZ2JuzqxZqT0xc6/c2rvp\nZh07jdLTw8aG0aNZv57bt7lxA19fPDzSScASEggLw8uLjh0pWpTq1Rk+nFWriI3N3J1Kl2bc\nOGWPxqBBfPNN2s64OqtUKXbvZuBA5fDFCwYMQHsdSt7P05NevfD1pWlTYmI0fTdj4wRQdkBX\nqcL169y9S1AQc+cybRrVqwMEBjJgAK6ulCpF5cq4uenEf++6LE+usYuJidmxY0dUVNSZM2dU\nZ+rWrVunTp1OnTrVqFFDu7FJkqRRFSsyaRKTJqWe6duXzZvp2pVBg2jXTmuPaBcsWBAQEDB2\n7Fjt3F4HqGbyVJ2sbt0iJCT93bXA5cssXszixQDVquHkhLMz7dplbgXajRusWsWuXaxdywc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yHbuMpHR0mD0bV1eNTimZmtK8Oc2bAyQl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\nRK5CYII=",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Parametric models\n",
    "library(flexsurv)\n",
    "weib_mod = flexsurvreg(Surv(time, status) ~ treatment + age + sh+ size + index, data = prost, dist = \"weibull\")\n",
    "exp_mod = flexsurvreg(Surv(time, status) ~ treatment + age + sh+ size + index, data = prost, dist = \"exp\")\n",
    "plot(weib_mod)\n",
    "lines(exp_mod, col=\"blue\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "91d994bc",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Using another dataset - Example 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "894b01c2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Call:\n",
       "coxph(formula = Surv(futime, status) ~ trt + stage + bili + riskscore, \n",
       "    data = udca1)\n",
       "\n",
       "  n= 169, number of events= 72 \n",
       "   (1 observation deleted due to missingness)\n",
       "\n",
       "              coef exp(coef) se(coef)      z Pr(>|z|)    \n",
       "trt       -1.01636   0.36191  0.25628 -3.966 7.31e-05 ***\n",
       "stage      0.03453   1.03514  0.28768  0.120   0.9045    \n",
       "bili       0.08971   1.09385  0.07827  1.146   0.2518    \n",
       "riskscore  0.30950   1.36275  0.16142  1.917   0.0552 .  \n",
       "---\n",
       "Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1\n",
       "\n",
       "          exp(coef) exp(-coef) lower .95 upper .95\n",
       "trt          0.3619     2.7631    0.2190    0.5981\n",
       "stage        1.0351     0.9661    0.5890    1.8192\n",
       "bili         1.0939     0.9142    0.9383    1.2752\n",
       "riskscore    1.3628     0.7338    0.9932    1.8699\n",
       "\n",
       "Concordance= 0.684  (se = 0.031 )\n",
       "Likelihood ratio test= 30.32  on 4 df,   p=4e-06\n",
       "Wald test            = 29.86  on 4 df,   p=5e-06\n",
       "Score (logrank) test = 31.47  on 4 df,   p=2e-06\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "### Exercise Cox Prop Hazards\n",
    "# Cox Proportional Hazards\n",
    "cox <- coxph(Surv(futime, status) ~ trt + stage + bili + riskscore, data = udca1)\n",
    "summary(cox)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "43b925b5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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HjhxZunTpww8/PHnyZBoe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\n/g990uqRgIGXDQAAAABJRU5ErkJggg==",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Getting a plot of the model \n",
    "autoplot(survfit(cox))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "4769ecc6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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AAAAcCpWCAPQp0nzd4L2afWhV4RsX76w8jJJZOfTqarajIbb9Shov48rjPU6qrE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\ngh0AQCT+P+IiUiCj/1qWAAAAAElFTkSuQmCC",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Standard Kaplan Meier plot to compare the treatments\n",
    "kmfit <- survfit(Surv(futime, status) ~ trt, data = udca1)\n",
    "autoplot(kmfit)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "18b42edb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Call:\n",
       "coxph(formula = Surv(futime, status) ~ trt, data = udca1)\n",
       "\n",
       "  n= 170, number of events= 72 \n",
       "\n",
       "       coef exp(coef) se(coef)     z Pr(>|z|)    \n",
       "trt -0.8624    0.4222   0.2443 -3.53 0.000416 ***\n",
       "---\n",
       "Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1\n",
       "\n",
       "    exp(coef) exp(-coef) lower .95 upper .95\n",
       "trt    0.4222      2.369    0.2615    0.6815\n",
       "\n",
       "Concordance= 0.614  (se = 0.029 )\n",
       "Likelihood ratio test= 12.99  on 1 df,   p=3e-04\n",
       "Wald test            = 12.46  on 1 df,   p=4e-04\n",
       "Score (logrank) test = 13.23  on 1 df,   p=3e-04\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Can we improve the concordance by eliminating non significant covariates?\n",
    "cox2 <- coxph(Surv(futime, status) ~ trt, data = udca1)\n",
    "summary(cox2)"
   ]
  }
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