## ----setup, include=FALSE-----------------------------------------------------
knitr::opts_chunk$set(collapse = TRUE, comment = "#>")

## ----conditional-logit, eval=FALSE--------------------------------------------
# matched_result <- conditional_logit_reg(
#   matched_data,
#   outcome = case,
#   exposures = exposure,
#   matched_set = matched_set,
#   adjust_for = c(age, smoking),
#   model_stats = TRUE
# )
# 
# matched_result
# matched_result$model_stats

## ----multilevel, eval=FALSE---------------------------------------------------
# clinic_result <- multilevel_reg(
#   clinic_data,
#   outcome = improved,
#   exposures = treatment,
#   group = clinic,
#   adjust_for = c(age, sex),
#   approach = "logit",
#   model_stats = TRUE
# )
# 
# clinic_result
# clinic_result$model_stats

## ----ordinal, eval=FALSE------------------------------------------------------
# recovery_data$recovery <- ordered(
#   recovery_data$recovery,
#   levels = c("Poor", "Fair", "Good", "Excellent")
# )
# 
# recovery_result <- ordinal_reg(
#   recovery_data,
#   outcome = recovery,
#   exposures = c(treatment, age),
#   adjust_for = sex,
#   model_stats = TRUE
# )
# 
# recovery_result
# recovery_result$assumption_tests

## ----multinomial, eval=FALSE--------------------------------------------------
# destination_data$destination <- stats::relevel(
#   destination_data$destination,
#   ref = "Home"
# )
# 
# destination_result <- multinomial_reg(
#   destination_data,
#   outcome = destination,
#   exposures = c(treatment, age),
#   adjust_for = frailty,
#   model_stats = TRUE
# )
# 
# destination_result
# names(destination_result$per_outcome)
# plot_reg(destination_result$per_outcome[["Rehabilitation"]])

## ----competing-risks, eval=FALSE----------------------------------------------
# cuminc_plot(
#   data_competing_risk,
#   time = follow_up_months,
#   event = outcome,
#   event_of_interest = Relapse,
#   censor_code = Censored,
#   by = treatment
# )
# 
# fine_gray_result <- competing_risk_reg(
#   data_competing_risk,
#   time = follow_up_months,
#   event = outcome,
#   event_of_interest = Relapse,
#   censor_code = Censored,
#   exposures = treatment,
#   adjust_for = c(age, stage),
#   model_stats = TRUE
# )
# 
# fine_gray_result

## ----downstream, eval=FALSE---------------------------------------------------
# modify_table(fine_gray_result, caption = "Relapse analysis")
# plot_reg(fine_gray_result)
# forest_reg(forest_df(fine_gray_result))
# save_table(fine_gray_result)