es.calc.linear {genpwr} | R Documentation |
Function to Calculate Effect Size for Linear Models
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')
[Package genpwr version 1.0.4 Index]