chest_clogit {chest}

Assessing confounding effects using conditional logistic regression models

Description

'chest_clogit' is used to fit many Conditional Logistic Regression models to assess confounding effects.

Usage

chest_clogit(
  crude,
  xlist,
  data,
  method = "exact",
  na_omit = TRUE,
  plus = "  + ",
  indicate = FALSE,
  ...
)

Arguments

crude

An object of formula for the initial model, generally crude model. However, any other variables can also be included here as the initial model.

xlist

A vector of characters with all variable names of potential confounders.

data

Data frame.

method

See 'clogit', default is the "exact" method.

na_omit

Remove all missing values, default: 'na_omit = TRUE'.

plus

Change the + sign before variable names.

indicate

indicate the calculation progress.

...

Further optional arguments.

Value

A table with effect estimates and their changes at all steps.

See Also

chest

'clogit' in 'survival'

Examples

vlist <- c("Age", "Sex", "Married", "Cancer", "CVD", "Education", "Income")
chest_clogit(
  crude = "Endpoint ~ Diabetes + strata(mid)",
  xlist = vlist, data = diab_df
)