calc.like.linear.log.envir.interaction {genpwr}

Function to calculate the standard deviation of y given x for linear models with logistic environment interaction

Description

Returns the standard deviation of y given x for linear models with logistic environment interaction

Usage

calc.like.linear.log.envir.interaction(
  beta_hat,
  MAF,
  P_e,
  ES_G,
  ES_E,
  ES_GE,
  sd_y_x_truth,
  sd_y_x_model,
  Test.Model,
  True.Model,
  reduced = F
)

Arguments

beta_hat

Effect sizes from MLE

MAF

Minor allele Frequency

P_e

Population prevalence of logistic environmental factor

ES_G

Genetic Effect size

ES_E

Environment Effect size

ES_GE

Environment x Genetic interaction Effect size

sd_y_x_truth

Standard deviation of y for the true model

sd_y_x_model

Standard deviation of y for the test model

Test.Model

Test model

True.Model

True model

reduced

logical, indicates whether the X matrix will be used for a reduced model

Value

The standard deviation of y given x for linear models with logistic environment interaction

Examples

beta_hat = linear.mles.log.envir.interaction(MAF = 0.1, P_e = 0.2, 
	ES_G = 1.2, ES_E = 1.3, ES_GE = 2, 
	Test.Model = "Dominant", True.Model = "Additive")
calc.like.linear.log.envir.interaction(beta_hat = beta_hat,
	MAF = 0.1, P_e = 0.2, ES_G = 1.2, ES_E = 1.3,
	ES_GE = 2, sd_y_x_truth = 9.947945, sd_y_x_model = 9.949468, 
	True.Model = "Additive", Test.Model="Dominant")