'Simulations for power analysis' presentation/mini workshop for the JCU CodeR group. See repo for slides and code to conduct your own simulation power analysis in R!
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Updated
Jul 18, 2022 - R
'Simulations for power analysis' presentation/mini workshop for the JCU CodeR group. See repo for slides and code to conduct your own simulation power analysis in R!
Eficácia do Ácido tranexâmico na redução de edema em cirurgias plásticas de face: projeto piloto
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.
Experiment Design, Random Assignment, Simulation for Power Analysis, Effect Size, Sample Size
ggplotting power curves from simr package
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 for the verification of possible Interleukin-6 circadian rhythm in Alpha-1 Antitrypsin deficient patients
An in-progress set of tools created to perform feature extraction and more on RTL files
R Shinyapp to calculate sample size for a given power
Simulate population dynamics and survey data that respond to stream hydrology using historical data from USGS stream gages.
Empirical Evaluation of the Resilience of Novel S-Box Implementations Against Power Side-Channel Attacks
Workshop on Sample Size Planning for Intensive Longitudinal Studies
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.
Power Measurement and Analysis
The data analysis code for the replication study CREP-21-39.
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.)
📈 Sample size estimation for the {pregnancy} project
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