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

template_forest_rsp generates correct expressions

Code
  res
Output
  $data
  {
      adrs <- 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(is_rsp = AVALC %in% c("CR", "PR")) %>% 
          dplyr::mutate(ARMCD = combine_levels(ARMCD, levels = c("ARM B", 
              "ARM C")))
      parent <- adsl %>% 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(ARMCD = combine_levels(ARMCD, levels = c("ARM B", 
              "ARM C")))
  }

  $summary
  {
      df <- extract_rsp_subgroups(variables = list(rsp = "is_rsp", 
          arm = "ARMCD", subgroups = c("SEX", "STRATA2"), strata = NULL), 
          data = adrs, conf_level = 0.95)
  }

  $table
  result <- rtables::basic_table() %>% tabulate_rsp_subgroups(df, 
      vars = c("n_tot", "n", "n_rsp", "prop", "or", "ci"), riskdiff = NULL)

  $plot
  $plot[[1]]
  f <- g_forest(tbl = result, col_symbol_size = NULL, font_size = 15, 
      as_list = TRUE)

  $plot[[2]]
  table <- f[["table"]] + ggplot2::labs(title = "Forest Plot of Best Overall Response for ")

  $plot[[3]]
  plot <- f[["plot"]] + ggplot2::labs(caption = "")

template_forest_rsp works with risk difference column added

Code
  res
Output
  $data
  {
      adrs <- 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(is_rsp = AVALC %in% c("CR", "PR")) %>% 
          dplyr::mutate(ARMCD = combine_levels(ARMCD, levels = c("ARM B", 
              "ARM C")))
      parent <- adsl %>% 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(ARMCD = combine_levels(ARMCD, levels = c("ARM B", 
              "ARM C")))
  }

  $summary
  {
      df <- extract_rsp_subgroups(variables = list(rsp = "is_rsp", 
          arm = "ARMCD", subgroups = c("SEX", "STRATA2"), strata = NULL), 
          data = adrs, conf_level = 0.95)
  }

  $table
  result <- rtables::basic_table() %>% tabulate_rsp_subgroups(df, 
      vars = c("n_tot", "or", "ci"), riskdiff = list(arm_x = NULL, 
          arm_y = NULL, format = "xx.x (xx.x - xx.x)", col_label = "Prop. Diff", 
          pct = TRUE))

  $plot
  $plot[[1]]
  f <- g_forest(tbl = result, col_symbol_size = NULL, font_size = 15, 
      as_list = TRUE)

  $plot[[2]]
  table <- f[["table"]] + ggplot2::labs(title = "Forest Plot of Best Overall Response for ")

  $plot[[3]]
  plot <- f[["plot"]] + ggplot2::labs(caption = "")