eval.power.binary.imbalanced: Estimate power for a binary variable in an imbalanced design

In MRCIEU/metaboprep: Metabolomics data preparation and processing pipeline

Estimate power for a binary variable in an imbalanced design

Description

This function allows you estimate power for a binary variable given a defined number of case samples, control samples, effect size, and significance threshold.

Usage

eval.power.binary.imbalanced(N_case, N_control, effect, alpha)

Arguments

N_case	a numeric vector of sample size of cases
N_control	a numeric vector of sample size of controls
effect	a numeric vector of effect size
alpha	a numeric vector of significance thresholds

Value

a matrix of paramater inputs and power estimates are returned as a matrix

Examples

eval.power.binary.imbalanced( N_case = 1000, 
 N_control = 1000, 
 effect = 0.01, 
 alpha = 0.05 )

eval.power.binary.imbalanced( N_case = c(1000, 2000), 
 N_control = c(1000, 2000), 
 effect = 0.01, 
 alpha = 0.05 )

MRCIEU/metaboprep documentation built on Jan. 28, 2023, 7:29 p.m.