genpwr.calc: Function to Calculate Power for Linear Models with logistic...
In genpwr: Power Calculations Under Genetic Model Misspecification

Description Usage Arguments Value Examples

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

genpwr.calc(
  calc,
  model,
  ge.interaction = NULL,
  N = NULL,
  Power = NULL,
  MAF = NULL,
  Alpha = 0.05,
  P_e = NULL,
  sd_e = NULL,
  sd_y = NULL,
  Case.Rate = NULL,
  k = NULL,
  OR = NULL,
  OR_G = NULL,
  OR_E = NULL,
  OR_GE = NULL,
  risk_allele = TRUE,
  ES = NULL,
  ES_G = NULL,
  ES_E = NULL,
  ES_GE = NULL,
  R2 = NULL,
  R2_G = NULL,
  R2_E = NULL,
  R2_GE = NULL,
  True.Model = "All",
  Test.Model = "All"
)

`calc`	What kind of calculation to perform? sample size ("ss"), power ("power"), or effect size ("es")
`model`	Distribution of the outcome variable? ("logistic" or "linear")
`ge.interaction`	If no environment interaction, should be NULL, otherwise should be "logistic" or "linear"
`N`	Vector of the desired sample size(s)
`Power`	Vector of the desired power(s)
`MAF`	Vector of minor allele frequencies
`Alpha`	the desired type 1 error rate(s)
`P_e`	Vector of proportions of the population with exposure to the environmental effect
`sd_e`	Standard deviation of the environmental variable
`sd_y`	Standard deviation of the outcome in the population (ignoring genotype). Either sd_y_x or sd_y must be specified.
`Case.Rate`	Case Rate of the outcome in the population (ignoring genotype). Either Case.Rate_x or Case.Rate must be specified.
`k`	Vector of the number of controls per case. Either k or Case.Rate must be specified.
`OR`	Vector of genetic odds ratios to detect in absence of environmental odds ratios
`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
`risk_allele`	Logical: If OR > 1, the allele is classified as a "risk allele"
`ES`	Vector of effect sizes (difference in means) to detect. Either ES or R2 must be specified.
`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.
`R2`	Vector of R-squared values to detect. Either ES or R2 must be specified.
`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 Either ES_G, ES_E, and ES_EG or R2_G, R2_E, and R2_EG must be specified.
`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'

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

pw <- genpwr.calc(calc = "power", model = "logistic", ge.interaction = "continuous",
	N=100, OR_G=2, OR_E=1.4, OR_GE=c(1.5, 2), 
	sd_e = 1.1, MAF=0.1, Case.Rate = 0.3, Alpha=0.05,
	True.Model="All", Test.Model=c("Dominant", "Recessive"))