calc.like.linear: Function to Calculate Log Likelihood for a Linear Regression...

Description Usage Arguments Value Examples

View source: R/likelihood_calc_function.R

Description

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

Usage

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calc.like.linear(beta, m, es_ab, es_bb, sd_y_x_model, sd_y_x_truth, model)

Arguments

beta

Vector of linear regression coefficients.

m

Minor allele frequency.

es_ab

effect size for mean AB - mean AA

es_bb

effect size for mean BB - mean AA

sd_y_x_model

The standard deviation of Y (the outcome) given X (predictors/genotype) under the test model.

sd_y_x_truth

The standard deviation of Y given X (predictors/genotype) given genotype under the true model.

model

The genetic model in the linear regression: "Dominant", "Additive", "Recessive", "2df" or "null"

Value

The log likelihood.

Examples

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calc.like.linear(beta = c(0.0000000, 0.1578947), m = 0.1, es_ab = 0, es_bb = 3, 
 sd_y_x_model = 0.9980797, sd_y_x_truth = 0.9544108, model = "Dominant")

genpwr documentation built on Sept. 18, 2019, 1:03 a.m.