Description Usage Arguments Value
View source: R/univariate_screen.r
Run univariate models on all observations variables with respect to response. Asseses p-value of model given LRT or Wald test. Returns all models or just models more significant than the given threshold: thresh.
1 2 3 |
df, |
a data.frame containing response and observations variables. Factors with more than 2 levels have only been implimented for test='LRT' |
observations, |
a character vector of the names of independent/observations variables in df |
response, |
a character vector of the names of dependent/response variables in df |
family, |
a character string indicating the family associated with the submitted model c('gaussian','binomial','poisson'...) |
model, |
a model associated for testing the variables c(glm,lm) |
interactions, |
a boolean indicating if interactions should be assessed. Default is False. |
test, |
a character string indicating Likelihood Ratio Test ('LRT') testing likelihood improvement of a model or Wald test ('Wald') testing coefficient > 0 |
thresh, |
a numeric value indicating the p-value cutoff for the univariate screening |
only_return_selected, |
a boolean value. If true, only models with p-value less than the threshold will be returned. Otherwise, all models will be returned. |
context_var, |
a character vector of variable(s) necessary for contextual assessment (e.g. age or time) |
a list of univariate models, attr(,'Pr') houses the significance of each model
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.