ss_linear_envir.calc.linear_outcome {genpwr} | R Documentation |
Function to Calculate Power for Linear Models with linear 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
ss_linear_envir.calc.linear_outcome(
pow = NULL,
MAF = NULL,
ES_G = NULL,
ES_E = NULL,
ES_GE = NULL,
sd_e = NULL,
R2_G = NULL,
R2_E = NULL,
R2_GE = NULL,
sd_y = NULL,
Alpha = 0.05,
True.Model = "All",
Test.Model = "All"
)
Arguments
pow |
Vector of the desired power(s) |
MAF |
Vector of minor allele frequencies |
ES_G |
Vector of genetic effect sizes (difference in means) to detect. Either ES_G, ES_E, and ES_EG or R2_G, R2_E, and R2_EG must be specified. |
ES_E |
Vector of environmental effect sizes (difference in means) to detect. Either ES_G, ES_E, and ES_EG or R2_G, R2_E, and R2_EG must be specified. |
ES_GE |
Vector of genetic/environment interaction effect sizes (difference in means) to detect. Either ES_G, ES_E, and ES_EG or R2_G, R2_E, and R2_EG must be specified. |
sd_e |
Standard deviation of the environmental variable |
R2_G |
Vector of genetic R-squared values to detect. Either ES_G, ES_E, and ES_EG or R2_G, R2_E, and R2_EG must be specified. |
R2_E |
Vector of environmental R-squared values to detect. Either ES_G, ES_E, and ES_EG or R2_G, R2_E, and R2_EG must be specified. |
R2_GE |
Vector of genetic/environment interaction R-squared values to detect. Either ES_G, ES_E, and ES_EG or R2_G, R2_E, and R2_EG must be specified. |
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
ss_linear_envir.calc.linear_outcome(pow = 0.8,
ES_G=0.5, ES_E=1.6, ES_GE=1.4,
sd_e = 1, MAF=0.28,
sd_y = 5,Alpha=0.05,
True.Model='All', Test.Model='All')