eh_test_subtype() to obtain a model fit, if factor variables are involved in the analysis it will be of interest to obtain overall p-values testing for differences across subtypes across all levels of the factor variable.
posthoc_factor_test() function allows for post-hoc testing of a factor variable.
# Load needed packages library(riskclustr) library(dplyr)
# create a new example dataset that contains a factor variable <- factor_data %>% subtype_data mutate( x4 = cut( x1,breaks = c(-3.4, -0.4, 0.3, 1.1, 3.8), include.lowest = T, labels = c("1st quart", "2nd quart", "3rd quart", "4th quart") ) )
# Fit the model using x4 in place of x1 <- eh_test_subtype( mod1 label = "subtype", M = 4, factors = list("x4", "x2", "x3"), data = factor_data, digits = 2 )
After we have the model fit, we can obtain the p-value testing all levels of
<- posthoc_factor_test( mypval fit = mod1, factor = "x4", nlevels = 4 )
The function returns both a formatted and unformatted p-value. The formatted p-value can be accessed as
$pval mypval#> [,1] #> [1,] "<.001"
The unformatted p-value can be accessed as
$pval_raw mypval#> [,1] #> [1,] 0