compute_sample_size: Sample size for Generalized Linear Models

In Dpananos/poweregg: A Package For GLM Power Calculations

Description

Calculate sample size required to meet minimial detectable effect given standard deviation of the predictor, multiple correlation, power, false positive rate, and variance of the outcome.

Usage

compute_sample_size(method_name, beta, sigma_x, mult_cor, power = 0.8,
  fpr = 0.05, ...)

Arguments

method_name	Name of GLM intended to be used. Function accepts: 'linear regression', 'logistic regression', 'cox regression', or 'poisson regression'
beta	Smallest effect to detect
sigma_x	Standard deviation of the predictor to which beta applies
mult_cor	Multiple correlation with other covariates
power	Desired statistical power, must be between 0 and 1 (default 0.8)
fpr	False positive rate, must bebetween 0 and 1 (Default 0.05)
...	arguments to variance function

Examples

samplesize(method_name='linear regression', 1,1,0,var_y=1)
samplesize(method_name='logistic regression', 1,1,0,p=0.5)
samplesize(method_name='cox regression', 1,1,0,prob_uncens=0.75)
samplesize(method_name='poisson regression', 1,1,0,disp=1)

Dpananos/poweregg documentation built on May 17, 2019, 5:25 a.m.