calc.like: Function to Calculate Log Likelihood for a Logistic...

In genpwr: Power Calculations Under Genetic Model Misspecification

Description

Convenience function to calculate the log likelihood of a specified model.

Usage

calc.like(beta, t, model)

Arguments

beta	Vector of logistic regression coefficients.
t	A 2x3 table of joint probabilities of disease and genotype. Rows = case vs. control, columns=genotype.
model	The genetic model in the logistic regression: "Dominant", "Additive", "Recessive", "2df" or "null"

Value

The log likelihood.

Examples

t <- rbind(c(0.2967437, 0.1806723, 0.02258404), 
 c(0.3432563, 0.1393277, 0.01741596))
calc.like(logistic.mles(t, "Dominant"), t, model="Dominant")

genpwr documentation built on March 31, 2021, 1:06 a.m.