tests/testthat/_snaps/tm_t_coxreg.md

In teal.modules.clinical: 'teal' Modules for Standard Clinical Outputs

template_coxreg generates correct univariate cox regression expressions

Code
  res
Output
  $data
  {
      anl <- adrs %>% dplyr::filter(ARMCD %in% c("ARM A", "ARM B", 
          "ARM C")) %>% dplyr::mutate(ARMCD = stats::relevel(ARMCD, 
          ref = "ARM A")) %>% dplyr::mutate(ARMCD = droplevels(ARMCD)) %>% 
          dplyr::mutate(event = 1 - CNSR) %>% dplyr::mutate(across(where(is.factor) & 
          NULL, droplevels)) %>% df_explicit_na(na_level = "<Missing>")
      control <- list(pval_method = "wald", ties = "efron", conf_level = 0.95, 
          interaction = FALSE)
  }

  $layout
  lyt <- rtables::basic_table(title = "Multi-Variable Cox Regression for OS", 
      main_footer = c("p-value method for Coxph (Hazard Ratio): wald", 
          "Ties for Coxph (Hazard Ratio): efron")) %>% rtables::append_topleft("OS") %>% 
      summarize_coxreg(variables = list(time = "AVAL", event = "event", 
          arm = "ARMCD", strata = "STRATA1"), control = list(pval_method = "wald", 
          ties = "efron", conf_level = 0.95, interaction = FALSE), 
          at = list(AGE = c(35, 45)), multivar = FALSE, .stats = c("n", 
              "hr", "ci", "pval"), na_str = "<Missing>")

  $table
  table <- rtables::build_table(lyt = lyt, df = anl)

template_coxreg generates correct univariate cox regression expressions with interactions

Code
  res
Output
  $data
  {
      anl <- adrs %>% dplyr::filter(ARMCD %in% c("ARM A", "ARM B", 
          "ARM C")) %>% dplyr::mutate(ARMCD = stats::relevel(ARMCD, 
          ref = "ARM A")) %>% dplyr::mutate(ARMCD = droplevels(ARMCD)) %>% 
          dplyr::mutate(event = 1 - CNSR) %>% dplyr::mutate(across(where(is.factor) & 
          NULL, droplevels)) %>% df_explicit_na(na_level = "<Missing>")
      control <- list(pval_method = "wald", ties = "efron", conf_level = 0.95, 
          interaction = TRUE)
  }

  $layout
  lyt <- rtables::basic_table(title = "Multi-Variable Cox Regression for OS", 
      main_footer = c("p-value method for Coxph (Hazard Ratio): wald", 
          "Ties for Coxph (Hazard Ratio): efron")) %>% rtables::append_topleft("OS") %>% 
      summarize_coxreg(variables = list(time = "AVAL", event = "event", 
          arm = "ARMCD", strata = "STRATA1"), control = list(pval_method = "wald", 
          ties = "efron", conf_level = 0.95, interaction = TRUE), 
          at = list(AGE = c(35, 45)), multivar = FALSE, .stats = c("n", 
              "hr", "ci", "pval", "pval_inter"), na_str = "<Missing>")

  $table
  table <- rtables::build_table(lyt = lyt, df = anl)

template_coxreg generates correct multivariate cox regression expressions

Code
  res
Output
  $data
  {
      anl <- adrs %>% dplyr::filter(ARM %in% c("A: Drug X", "B: Placebo", 
          "C: Combination")) %>% dplyr::mutate(ARM = stats::relevel(ARM, 
          ref = "A: Drug X")) %>% dplyr::mutate(ARM = droplevels(ARM)) %>% 
          dplyr::mutate(ARM = combine_levels(x = ARM, levels = c("B: Placebo", 
              "C: Combination"))) %>% dplyr::mutate(event = 1 - 
          CNSR) %>% dplyr::mutate(across(where(is.factor) & c("AGE", 
          "SEX"), droplevels)) %>% df_explicit_na(na_level = "<Missing>")
  }

  $layout
  lyt <- rtables::basic_table(title = "Cox Regression for OS", 
      main_footer = c("p-value method for Coxph (Hazard Ratio): wald", 
          "Ties for Coxph (Hazard Ratio): exact")) %>% rtables::append_topleft("OS") %>% 
      summarize_coxreg(variables = list(time = "AVAL", event = "event", 
          arm = "ARM", covariates = c("AGE", "SEX")), control = list(pval_method = "wald", 
          ties = "exact", conf_level = 0.95, interaction = FALSE), 
          multivar = TRUE, .stats = c("hr", "ci", "pval"), na_str = "<Missing>")

  $table
  {
      table <- rtables::build_table(lyt = lyt, df = anl)
  }

teal.modules.clinical documentation built on April 4, 2025, 12:35 a.m.