es.calc.linear: Function to Calculate Effect Size for Linear Models

In genpwr: Power Calculations Under Genetic Model Misspecification

Description

Calculates the detectable effect size/regression coefficient, at a given sample size, N, and power, with type 1 error rate, Alpha

Usage

es.calc.linear(
  power = NULL,
  N = NULL,
  MAF = NULL,
  sd_y = NULL,
  Alpha = 0.05,
  True.Model = "All",
  Test.Model = "All"
)

Arguments

power	Vector of the desired power(s)
N	Vector of the desired sample size(s)
MAF	Vector of minor allele frequencies
sd_y	Standard deviation of the outcome in the population (ignoring genotype). Either sd_y_x or sd_y must be specified.
Alpha	the desired type 1 error rate(s)
True.Model	A vector specifying the true underlying genetic model(s): 'Dominant', 'Additive', '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

es <- es.calc.linear(N=1000,power=0.8,
    MAF=0.1, sd_y = 1, Alpha=0.05,
    True.Model='All', Test.Model='All')

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