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

template_fit_mmrm works as expected when not combining comparison arms

Code
  res
Output
  $data
  {
      anl <- adqs %>% 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)) %>% 
          df_explicit_na(na_level = default_na_str())
      adsl <- 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)) %>% 
          df_explicit_na(na_level = default_na_str())
  }

  $fit
  fit <- tern.mmrm::fit_mmrm(vars = list(response = "AVAL", covariates = NULL, 
      id = "USUBJID", arm = "ARMCD", visit = "AVISIT"), data = anl, 
      conf_level = 0.95, method = "Satterthwaite", cor_struct = "unstructured", 
      weights_emmeans = "proportional", parallel = FALSE)

template_fit_mmrm works as expected when combining combination arms

Code
  res
Output
  $data
  {
      anl <- adqs %>% 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"))) %>% df_explicit_na(na_level = default_na_str())
      adsl <- 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"))) %>% df_explicit_na(na_level = default_na_str())
  }

  $fit
  fit <- tern.mmrm::fit_mmrm(vars = list(response = "AVAL", covariates = c("SEX", 
  "BASE", "AVISIT"), id = "USUBJID", arm = "ARMCD", visit = "AVISIT"), 
      data = anl, conf_level = 0.95, method = "Satterthwaite", 
      cor_struct = "unstructured", weights_emmeans = "proportional", 
      parallel = TRUE)

template_mmrm_tables works as expected

Code
  res
Output
  $layout
  lyt <- rtables::basic_table(show_colcounts = TRUE) %>% rtables::split_cols_by(var = "ARMCD", 
      ref_group = "ARM A") %>% rtables::split_rows_by("AVISIT") %>% 
      append_varlabels(ANL, "AVISIT") %>% tern.mmrm::summarize_lsmeans(show_relative = "increase") %>% 
      rtables::append_topleft(paste0("  ", "ALBUMIN"))

  $cov_matrix
  {
      covariance_table <- tern.mmrm::as.rtable(fit_mmrm, type = "cov")
      subtitles(covariance_table) <- NULL
  }

template_mmrm_tables works as expected when arm is not considered in the model

Code
  res
Output
  $layout
  lyt <- rtables::basic_table(show_colcounts = FALSE) %>% rtables::add_overall_col("All Patients") %>% 
      rtables::split_rows_by("AVISIT") %>% tern.mmrm::summarize_lsmeans(arms = FALSE) %>% 
      rtables::append_topleft(paste0("  ", "ALBUMIN"))

  $cov_matrix
  {
      covariance_table <- tern.mmrm::as.rtable(fit_mmrm, type = "cov")
      subtitles(covariance_table) <- NULL
  }

template_mmrm_plots works as expected

Code
  res
Output
  $lsmeans_plot
  {
      lsmeans_plot <- tern.mmrm::g_mmrm_lsmeans(fit_mmrm, select = c("estimates", 
      "contrasts"), width = 0.6, show_pval = FALSE, titles = if (is.null(fit_mmrm$vars$arm)) {
          c(estimates = paste("Adjusted mean of", fit_mmrm$labels$response, 
              " at visits"), contrasts = " ")
      }
      else {
          c(estimates = paste("Adjusted mean of", fit_mmrm$labels$response, 
              "by treatment at visits"), contrasts = paste0("Differences of ", 
              fit_mmrm$labels$response, " adjusted means vs. control ('", 
              fit_mmrm$ref_level, "')"))
      })
      lsmeans_plot
  }

  $diagnostic_plot
  {
      diagnostic_plot <- tern.mmrm::g_mmrm_diagnostic(fit_mmrm, 
          type = "fit-residual", z_threshold = NULL)
      diagnostic_plot
  }