Simulation-based power analysis library

Solution in the form of a tutorial article wherein the key decisions made in conducting a CFA are validated through recent literature and presented within a dynamic document framework.

📈 Sample size estimation for the {pregnancy} project

This repository explores the activation patterns of A2 noradrenergic neurons in fear-conditioned rats, using statistical analyses like t-tests and linear regression in R. It focuses on the differences in dopamine β-hydroxylase (DbH) neuron activation between various environmental conditions.

An in-progress set of tools created to perform feature extraction and more on RTL files

Study power behaviors of Bayesian Network Meta-analysis (NMA) using simulations and real-world case studies

Python package for conducting power analysis for experiments using regression and/or clustered data.

Experimental design framework for scRNAseq population studies (eQTL and DE)

This python project is a helper package that uses power analysis to calculate required sample size for any experiment

Анализ групного датасета по игровой зависимости, проверка психологических гипотез с помощью ряда статистических методов: анализ мощности, анализ латентных классов, анова фреквентистская VS байесовская

Hi-voltage, Hi-current isolated multirange AFE for MIO168 module

This incomplete repository is used to facilitate the consultation of individual files in this project. Only files smaller than 100 MB are available here. The complete project is available at https://doi.org/10.17605/OSF.IO/GT5UF.

Matched Markets is a Python library for design and analysis of Geo experiments using Matched Markets and Time Based Regression.

Using R tools like ggplot2 and dplyr, analyzed small business data to understand uptake patterns for federal aid. Employed logistic regression and decision trees to pinpoint key predictors. Explored strategies like mailer campaigns to boost application rates and conducted power analysis for potential randomized trials.

Power analysis is essential to optimize the design of RNA-seq experiments and to assess and compare the power to detect differentially expressed genes. PowsimR is a flexible tool to simulate and evaluate differential expression from bulk and especially single-cell RNA-seq data making it suitable for a priori and posterior power analyses.

The project aims to explore whether advertisements have an impact on customer buying activity to optimize their effectiveness in encouraging purchases.

Miscellaneous Esoteric Statistical Scripts - an R package

Shiny web app to run power analysis for RNA-Seq experiments.

Visualise the output from allFit(), to look at the parameters for a set of predictors across a set of optimizers (e.g., bobyqa, Nelder-Mead, etc.)

ggplotting power curves from simr package