Contents
How to calculate power of Fisher exact test?
Calculate by simulation the power of Fisher’s exact test for comparing two proportions given two margin counts. first proportion to be compared. second proportion to be compared. first sample size.
How to calculate the proportion of a sample?
Compare proportion with a dichotomous outcome between two samples, using the Chi-squared statistic (or z test). Your study includes Group 1 (exposed or active treatment) and Group 0 (unexposed or control treatment).
Which is the best test for single proportions?
Tests of single proportions are generally based on the binomial distribution with size parameter N and probability parameter p. For large sample sizes, this can be well approximated by a normal distribution with mean N*p and variance N*p (1 − p).
Which is the exact conditional test for two independent proportions?
Fisher’s Exact Conditional Test for Two Proportions Fixed Scenario Elements Distribution Exact conditional Method Walters normal approximation Group 1 Proportion 0.3 Group 2 Proportion 0.15 Nominal Power 0.8 Number of Sides 2 Alpha 0.05 Computed N Per Group Actual N Per Power Group 0.800 132
How to simulate Fisher’s exact test in R?
For (considerably) more information on power analyses, and simulating them in R, you should read my answer here: Simulation of logistic regression power analysis – designed experiments. In this case, I will just give a quick, adapted version for dealing with Fisher’s exact test.
When to use Fisher’s exact test in statology?
Fisher’s Exact Test is a test of significance that is used in place of a Chi Square Test in 2×2 tables when the sample sizes are small. This tutorial explains how to conduct Fisher’s Exact Test in R.
How many iterations does Fisher’s exact test turn up?
Given how far your data diverge from the null hypothesis in Fisher’s exact test, and the amount of data you have, this simulation does not turn up a single type II error in 10,000 iterations.