## ----reg-setup, message=FALSE, warning=FALSE----------------------------------
library(gtregression)
library(dplyr)

data("data_birthwt", package = "gtregression")

birthwt_data <- data_birthwt |>
  mutate(
    race = factor(race, levels = c(1, 2, 3),
                  labels = c("White", "Black", "Other")),
    smoke = factor(smoke, levels = c(0, 1), labels = c("No", "Yes")),
    ht = factor(ht, levels = c(0, 1), labels = c("No", "Yes")),
    ui = factor(ui, levels = c(0, 1), labels = c("No", "Yes")),
    low = factor(low, levels = c(0, 1), labels = c("Normal BW", "Low BW")),
    ptl_cat = factor(ifelse(ptl > 0, "Yes", "No"), levels = c("No", "Yes")),
    ftv_cat = factor(case_when(
      ftv == 0 ~ "None",
      ftv == 1 ~ "One",
      ftv >= 2 ~ "Two or more"
    ), levels = c("None", "One", "Two or more"))
  )

birthwt_exposures <- c(
  "age", "lwt", "race", "smoke", "ht", "ui", "ptl_cat", "ftv_cat"
)

attr(birthwt_data$age, "label") <- "Maternal age"
attr(birthwt_data$lwt, "label") <- "Maternal weight"
attr(birthwt_data$race, "label") <- "Maternal race"
attr(birthwt_data$smoke, "label") <- "Smoking during pregnancy"
attr(birthwt_data$ht, "label") <- "Hypertension"
attr(birthwt_data$ui, "label") <- "Uterine irritability"
attr(birthwt_data$ptl_cat, "label") <- "Previous preterm labour"
attr(birthwt_data$ftv_cat, "label") <- "First trimester visits"

## ----uni-logit, message=FALSE, warning=FALSE----------------------------------
birthwt_uni <- uni_reg(
  data = birthwt_data,
  outcome = "low",
  exposures = birthwt_exposures,
  approach = "logit",
  theme = clinical
)

birthwt_uni

## ----multi-full, message=FALSE, warning=FALSE---------------------------------
birthwt_full <- multi_reg(
  data = birthwt_data,
  outcome = low,
  exposures = c("age", "lwt", "race", "smoke", "ht", "ui"),
  approach = logit,
  theme = clinical
)

birthwt_full

## ----multi-adjusted, message=FALSE, warning=FALSE-----------------------------
birthwt_multi <- multi_reg(
  data = birthwt_data,
  outcome = low,
  exposures = c("smoke", "ht", "ui", "ptl_cat", "ftv_cat"),
  adjust_for = c("age", "lwt", "race"),
  approach = logit,
  theme = striped
)

birthwt_multi

## ----model-stats, message=FALSE, warning=FALSE--------------------------------
birthwt_uni_stats <- uni_reg(
  data = birthwt_data,
  outcome = low,
  exposures = birthwt_exposures,
  approach = logit,
  model_stats = TRUE
)

birthwt_uni_stats$model_stats

## ----adjusted-model-stats, message=FALSE, warning=FALSE-----------------------
birthwt_multi_stats <- multi_reg(
  data = birthwt_data,
  outcome = low,
  exposures = c("smoke", "ht", "ui", "ptl_cat"),
  adjust_for = c("age", "lwt", "race"),
  approach = logit,
  model_stats = TRUE
)

birthwt_multi_stats$model_stats

## ----reg-risk-ratio, message=FALSE, warning=FALSE-----------------------------
uni_reg(
  data = birthwt_data,
  outcome = low,
  exposures = c("smoke", "ht", "ui", "ptl_cat"),
  approach = logbinomial
)

## ----reg-firth, message=FALSE, warning=FALSE----------------------------------
data("data_endometrial", package = "gtregression")

endometrial_data <- data_endometrial |>
  mutate(
    HG = factor(HG, levels = c(0, 1),
                labels = c("Low grade", "High grade")),
    NV = factor(NV, levels = c(0, 1), labels = c("Absent", "Present"))
  )

multi_reg(
  data = endometrial_data,
  outcome = HG,
  exposures = c(NV, PI, EH),
  approach = firth
)

## ----cox-setup, message=FALSE, warning=FALSE----------------------------------
data("data_lungcancer", package = "gtregression")

lung_data <- data_lungcancer |>
  mutate(
    trt = factor(trt, levels = c(1, 2),
                 labels = c("Standard treatment", "Test treatment")),
    prior = factor(prior, levels = c(0, 10), labels = c("No", "Yes"))
  )

attr(lung_data$trt, "label") <- "Treatment group"
attr(lung_data$celltype, "label") <- "Cancer cell type"
attr(lung_data$karno, "label") <- "Karnofsky performance score"
attr(lung_data$age, "label") <- "Age"
attr(lung_data$prior, "label") <- "Prior therapy"

## ----cox-crude, message=FALSE, warning=FALSE----------------------------------
lung_hr <- cox_reg(
  data = lung_data,
  time = time,
  event = status,
  exposures = c("trt", "celltype", "karno", "age"),
  theme = clinical
)

lung_hr

## ----cox-adjusted, message=FALSE, warning=FALSE-------------------------------
lung_adj_hr <- cox_reg(
  data = lung_data,
  time = time,
  event = status,
  exposures = c(trt, celltype, prior),
  adjust_for = c(age, karno),
  model_stats = TRUE,
  theme = striped
)

lung_adj_hr
lung_adj_hr$model_stats

## ----cox-interaction, message=FALSE, warning=FALSE----------------------------
cox_interaction <- cox_reg(
  data = lung_data,
  time = time,
  event = status,
  exposures = trt,
  adjust_for = c(age, karno),
  interaction = trt*prior
)

cox_interaction

## ----surv-crude, message=FALSE, warning=FALSE---------------------------------
lung_time_ratio <- surv_reg(
  data = lung_data,
  time = time,
  event = status,
  exposures = c("trt", "celltype", "karno", "age"),
  distribution = weibull,
  theme = clinical
)

lung_time_ratio

## ----surv-adjusted, message=FALSE, warning=FALSE------------------------------
lung_adj_time_ratio <- surv_reg(
  data = lung_data,
  time = time,
  event = status,
  exposures = c(trt, celltype, prior),
  adjust_for = c(age, karno),
  distribution = lognormal,
  model_stats = TRUE,
  theme = striped
)

lung_adj_time_ratio
lung_adj_time_ratio$model_stats

## ----surv-interaction, message=FALSE, warning=FALSE---------------------------
surv_interaction <- surv_reg(
  data = lung_data,
  time = time,
  event = status,
  exposures = trt,
  adjust_for = c(age, karno),
  interaction = trt*prior,
  distribution = weibull
)

surv_interaction

## ----reg-linear, message=FALSE, warning=FALSE---------------------------------
birthwt_linear <- multi_reg(
  data = birthwt_data,
  outcome = bwt,
  exposures = c("age", "lwt", "race", "smoke", "ht", "ui"),
  approach = linear
)

birthwt_linear