GE_BICS | R Documentation |
A function to perform inference on the GxE interaction regression coefficient. Shows better small sample performance than comparable methods.
GE_BICS(outcome, design_mat, num_boots = 1000, desired_coef, outcome_type, check_singular = FALSE)
outcome |
The outcome vector |
design_mat |
The design matrix of covariates |
num_boots |
The number of bootstrap resamples to perform - we suggest 1000 |
desired_coef |
The column in the design matrix holding the interaction covariate |
outcome_type |
Either 'D' for dichotomous outcome or 'C' for continuous outcome |
check_singular |
Make sure the design matrix can be inverted for variance estimation |
The p-value for the interaction effect
E <- rnorm(n=500) G <- rbinom(n=500, size=2, prob=0.3) design_mat <- cbind(1, G, E, G*E) outcome <- rnorm(500) GE_BICS(outcome=outcome, design_mat=design_mat, desired_coef=4, outcome_type='C')
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.