LRcat: Compute Power for Logistic Regression with a Single...

In pwr2ppl: Power Analyses for Common Designs (Power to the People)

Compute Power for Logistic Regression with a Single Categorical Predictor

Description

Compute Power for Logistic Regression with a Single Categorical Predictor

Usage

LRcat(p0 = NULL, p1 = NULL, prop = 0.5, alpha = 0.05, power, R2 = 0)

Arguments

p0	Probability of a Desirable Outcome in the Control Condition
p1	Probability of a Desirable Outcome in the Treatment Condition
prop	Proportion in the Treatment Condition
alpha	Type I error (default is .05)
power	Desired Power
R2	How Well Predictor of Interest is Explained by Other Predictors (default is 0)

Value

Power for Logistic Regression with a Single Categorical Predictor

Examples

LRcat(p0=.137,p1=.611,prop =.689,power=.95)

pwr2ppl documentation built on Sept. 6, 2022, 5:06 p.m.