# import data
library(splines)
data(kidney)
age <- kidney$age
sex <- kidney$sex
kidexpr <- kidney$kidexpr
cov <- data.frame(sex = sex, age = age)
# create models
null_model <- ~sex
full_model <- ~sex + ns(age, df = 4)
# create deSet object from data
de_obj <- build_models(data = kidexpr, cov = cov, null.model = null_model,
full.model = full_model)
# lrt method
de_lrt <- lrt(de_obj, nullDistn = "normal")
# to generate p-values from bootstrap
de_lrt <- lrt(de_obj, nullDistn = "bootstrap", bs.its = 30)
# input a deFit object directly
de_fit <- fit_models(de_obj, stat.type = "lrt")
de_lrt <- lrt(de_obj, de.fit = de_fit)
# summarize object
summary(de_lrt)
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