df2.ll.linear {genpwr} | R Documentation |
Function to Calculate 2 Degree of Freedom Log Likelihood for a Linear Regression Model
Description
Calculates the log likelihood for a given set of linear regression coefficients under a the 2df model.
Usage
df2.ll.linear(beta, m, es, sd_y_x_model, sd_y_x_truth)
Arguments
beta |
Vector of linear regression coefficients. |
m |
Minor allele frequency. |
es |
Vector of effect sizes with two elements, (mean AB - mean AA) and (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. |
Value
The log likelihood.
Examples
df2.ll.linear(beta = c(0, 0, 3), m = 0.1, es = c(0,3),
sd_y_x_model = 0.9544108, sd_y_x_truth = 0.9544108)
[Package genpwr version 1.0.4 Index]