power_envir.calc: Function to Calculate Power for Logistic Models with...

In genpwr: Power Calculations Under Genetic Model Misspecification

Description

Calculates the power to detect an difference in means/effect size/regression coefficient, at a given sample size, N, with type 1 error rate, Alpha

Usage

power_envir.calc(
  N = NULL,
  Case.Rate = NULL,
  k = NULL,
  MAF = NULL,
  OR_G = NULL,
  OR_E = NULL,
  OR_GE = NULL,
  P_e = NULL,
  Alpha = 0.05,
  True.Model = "All",
  Test.Model = "All"
)

Arguments

N	Vector of the desired sample size(s)
Case.Rate	proportion of cases in the sample (cases/(cases + controls)).
k	Vector of the number of controls per case. Either k or Case.Rate must be specified.
MAF	Vector of minor allele frequencies
OR_G	Vector of genetic odds ratios to detect
OR_E	Vector of environmental odds ratios to detect
OR_GE	Vector of genetic/environmental interaction odds ratios to detect
P_e	Vector of proportions of the population with exposure to the environmental effect
Alpha	the desired type 1 error rate(s)
True.Model	A vector specifying the true underlying genetic model(s): 'Dominant', 'Additive1', 'Additive2', 'Recessive' or 'All'
Test.Model	A vector specifying the assumed genetic model(s) used in testing: 'Dominant', 'Additive', 'Recessive' or 'All'

Value

A data frame including the power for all combinations of the specified parameters (Case.Rate, ES, Power, etc)

Examples

pw <- power_envir.calc(P_e = 0.2, MAF = 0.1, N = 200, Case.Rate = 0.5, Alpha = 0.05, 
	OR_G = 1.5, OR_E = 2, OR_GE = 1.8, Test.Model = "All", True.Model = "All")

genpwr documentation built on March 31, 2021, 1:06 a.m.