power_envir.calc {genpwr} | R Documentation |
Function to Calculate Power for Logistic Models with Environment Interaction
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")