From f0aa8110a5deb47be8ae21e35bff08f746ce0d0f Mon Sep 17 00:00:00 2001
From: smritia <smriti.anand@pfizer.com>
Date: Wed, 18 Sep 2024 05:26:07 +0000
Subject: [PATCH] Migration from tlfcarver to minimise issues

---
 R/dataset_merge.R                     | 134 +++++++++++++
 R/graph_utils.R                       |   8 +-
 tests/testthat/test-ae_volcano_plot.R |  85 ++++++++
 tests/testthat/test-dataset_merge.R   |  54 +++++
 tests/testthat/test-forest_plot.R     | 243 +++++++++++-----------
 tests/testthat/test-mcatstat.R        | 278 +++++++++++++-------------
 tests/testthat/test-mdisplay.R        | 148 --------------
 tests/testthat/test-risk_stat.R       | 215 +++++++++++---------
 tests/testthat/test-volcano_plot.R    | 113 -----------
 9 files changed, 662 insertions(+), 616 deletions(-)
 create mode 100644 R/dataset_merge.R
 create mode 100644 tests/testthat/test-ae_volcano_plot.R
 create mode 100644 tests/testthat/test-dataset_merge.R
 delete mode 100644 tests/testthat/test-mdisplay.R
 delete mode 100644 tests/testthat/test-volcano_plot.R

diff --git a/R/dataset_merge.R b/R/dataset_merge.R
new file mode 100644
index 0000000..bdb5f0c
--- /dev/null
+++ b/R/dataset_merge.R
@@ -0,0 +1,134 @@
+# Copyright 2024 Pfizer Inc
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#' Merge Datasets
+#'
+#' @param ... Datasets to be merged.
+#' @param byvars By variables required to perform merge.
+#' @param subset Dataset specific subset conditions as `list`, default is `NULL`.
+#' Has to be specified in the same order of datasets to be merged
+#'
+#' @return A `data.frame`
+#' @export
+#'
+#' @examples
+#' dataset_merge(
+#'   lab_data$adsl,
+#'   lab_data$adlb,
+#'   byvars = "STUDYID~USUBJID~SUBJID",
+#'   subset = list("SEX=='F'", "PARAMCD == 'L00021S'")
+#' )
+#'
+#' dataset_merge(
+#'   lab_data$adsl,
+#'   lab_data$adlb,
+#'   byvars = "STUDYID~USUBJID~SUBJID",
+#'   subset = list("SEX=='F'", NA_character_)
+#' )
+#'
+#' dataset_merge(
+#'   lab_data$adsl,
+#'   lab_data$adlb,
+#'   byvars = "STUDYID~USUBJID~SUBJID",
+#'   subset = list(NA_character_, "PARAMCD == 'L00021S'")
+#' )
+#'
+#' dataset_merge(
+#'   lab_data$adsl,
+#'   lab_data$adlb,
+#'   byvars = "STUDYID~USUBJID~SUBJID",
+#'   subset = list("USUBJID == 'XYZ1 1003 10031009'", NA_character_)
+#' )
+#'
+#' dataset_merge(
+#'   waterfall_plot_data$adrs,
+#'   waterfall_plot_data$adtr,
+#'   byvars = "STUDYID~USUBJID~TRT01P",
+#'   subset = list("PARAMCD == 'BOR_C'", NA_character_)
+#' )
+#'
+#' ## more than 2 datasets
+#'
+#' dataset_merge(
+#'   dplyr::filter(lab_data$adsl, USUBJID == "XYZ1 1003 10031009"),
+#'   lab_data$adsl,
+#'   lab_data$adlb,
+#'   byvars = "STUDYID~USUBJID~SUBJID"
+#' )
+#'
+dataset_merge <- function(..., byvars, subset = NULL) {
+  dfs <- list2(...)
+  stopifnot("At least two datasets required for merging" = length(dfs) >= 2)
+  byvars <- str_to_vec(byvars)
+  if (!every(dfs, \(x) all(byvars %in% names(x)))) stop("`byvars` not present")
+
+  if (length(subset) > 0) {
+    stopifnot("Length of subsets and datasets should be equal" = length(dfs) == length(subset))
+    if (every(subset, is.na)) stop("All subsets cannot be `NA`, use `subset = NULL` instead")
+    dfs <- map(seq_along(dfs), \(i) {
+      df_sub <- dfs[[i]]
+      if (!is.na(subset[[i]])) {
+        df_sub <- df_sub |>
+          filter(!!!parse_exprs(subset[[i]]))
+      }
+      df_sub
+    })
+  }
+
+  df_list <- map(seq_along(dfs), \(x) {
+    out <- dfs[[x]]
+    if (x < length(dfs)) {
+      out <- out |>
+        select(all_of(union(byvars, setdiff(
+          names(dfs[[x]]), names(dfs[[x + 1]])
+        ))))
+    }
+    out
+  })
+  reduce(df_list, left_join, byvars)
+}
+
+#' Merge adsl dataset with the analysis dataset
+#'
+#' @param adsl adsl dataset
+#' @param adsl_subset population variable subset condition
+#' @param dataset_add analysis dataset
+#'
+#' @return merged dataset
+#' @export
+#'
+#' @examples
+#' data(lab_data)
+#'
+#' adsl_merge(
+#'   adsl = lab_data$adsl,
+#'   adsl_subset = "SAFFL=='Y'",
+#'   dataset_add = lab_data$adlb
+#' )
+#'
+adsl_merge <- function(adsl = NULL, adsl_subset = "", dataset_add = NULL) {
+  stopifnot(length(adsl) > 0)
+  stopifnot(nrow(adsl) > 0)
+  stopifnot(length(dataset_add) > 0)
+
+  if (adsl_subset != "" && !is.na(adsl_subset)) {
+    adsl <- adsl |>
+      filter(!!!parse_exprs(adsl_subset))
+  }
+
+  byvars <- grep("STUDYID|USUBJID|SUBJID", names(dataset_add), value = TRUE)
+
+  adsl |>
+    select(all_of(c(byvars, setdiff(names(adsl), names(dataset_add))))) |>
+    left_join(dataset_add, by = byvars)
+}
diff --git a/R/graph_utils.R b/R/graph_utils.R
index d9d2b95..42b50d1 100644
--- a/R/graph_utils.R
+++ b/R/graph_utils.R
@@ -21,7 +21,7 @@
 #' @export
 #'
 #' @examples
-#' library(tlfcarver)
+#' library(carver)
 #' library(ggplot2)
 #' ggplot(data = mtcars, mapping = aes(x = mpg, y = hp)) +
 #'   geom_point() +
@@ -160,7 +160,7 @@ g_seriessym <- function(gdata,
 #' @export
 #'
 #' @examples
-#' library(tlfcarver)
+#' library(carver)
 #' empty_plot()
 empty_plot <- function(message = "No data available for these values",
                        fontsize = 8) {
@@ -205,7 +205,7 @@ def_axis_spec <- function(arg, vec, val) {
 #' @export
 #'
 #' @examples
-#' library(tlfcarver)
+#' library(carver)
 #'
 #' plot_axis_opts(
 #'   xlinearopts = list(
@@ -600,7 +600,7 @@ plot_title_nsubj <- function(datain, plot_data, by) {
 #' @export
 #'
 #' @examples
-#' library(tlfcarver)
+#' library(carver)
 #' MPG <- ggplot2::mpg
 #' MPG[["cyl"]] <- as.character(MPG[["cyl"]])
 #' tbl_to_plot(
diff --git a/tests/testthat/test-ae_volcano_plot.R b/tests/testthat/test-ae_volcano_plot.R
new file mode 100644
index 0000000..45b389b
--- /dev/null
+++ b/tests/testthat/test-ae_volcano_plot.R
@@ -0,0 +1,85 @@
+data("ae_risk")
+vaxis_opts <- ae_volcano_opts(
+  datain = ae_risk,
+  statistic = "Risk Ratio",
+  trt1_label = "Control",
+  trt2_label = "Exposure",
+  pvalue_trans = "-log10",
+  xref_offset = 1
+)
+axis_opts <- plot_axis_opts(
+  ylinearopts = vaxis_opts$ylinearopts,
+  yaxis_scale = vaxis_opts$yaxis_scale,
+  xaxis_label = vaxis_opts$xaxis_label,
+  yaxis_label = vaxis_opts$yaxis_label
+)
+
+test_that("Test 1: Volcano plot Options works", {
+  expect_type(vaxis_opts, "list")
+  expect_named(
+    vaxis_opts,
+    c("xaxis_label", "yaxis_label", "ylinearopts", "yaxis_scale", "xref")
+  )
+  expected <- list(
+    xaxis_label = "<--- Favors Control (N=69) ---- Favors Exposure (N=79) --->\nRisk Ratio",
+    yaxis_label = "-log10 p-value",
+    ylinearopts = list(breaks = as.numeric(paste0("1e-", 0:20)), labels = as.character(0:20)),
+    yaxis_scale = reverselog_trans(10),
+    xref = c(1, 0, 2)
+  )
+  expect_equal(vaxis_opts, expected)
+  vaxis_opts2 <- ae_volcano_opts(
+    datain = ae_risk,
+    pvalue_trans = "none"
+  )
+  expected2 <- list(
+    xaxis_label = "<--- Favors Control (N=69) ---- Favors Exposure (N=79) --->\nRisk Ratio",
+    yaxis_label = "p-value",
+    ylinearopts = list(
+      breaks = c(0.05, 0, rep(1, 10) / 10^(9:0)),
+      labels = as.character(c(0.05, 0, rep(1, 10) / 10^(9:0)))
+    ),
+    yaxis_scale = "identity",
+    xref = c(1, 0, 2)
+  )
+  expect_equal(vaxis_opts2, expected2)
+})
+
+test_that("Test 1: Volcano plot with standard inputs", {
+  volcano_test <- ae_volcano_plot(
+    datain = ae_risk,
+    axis_opts = axis_opts,
+    legend_opts = list(label = "", pos = "bottom", dir = "horizontal"),
+    xref = vaxis_opts$xref,
+    pvalue_sig = 0.05
+  )
+  expect_type(volcano_test, "list")
+  expect_true("ggplot" %in% class(volcano_test))
+  expect_snapshot(volcano_test[["mapping"]])
+  expect_snapshot(volcano_test[["labels"]])
+  volcano_test2 <- ae_volcano_plot(
+    datain = ae_risk,
+    axis_opts = axis_opts,
+    xref = vaxis_opts$xref,
+    pvalue_sig = 0.004
+  )
+  purrr::walk(
+    volcano_test2$layers,
+    \(x) expect_snapshot(x$aes_params)
+  )
+})
+
+test_that("Test 2: Volcano plot with interactive output", {
+  volcano_test <- ae_volcano_plot(
+    datain = ae_risk,
+    axis_opts = axis_opts,
+    legend_opts = list(label = "", pos = "bottom", dir = "horizontal"),
+    xref = vaxis_opts$xref,
+    pvalue_sig = 0.05,
+    interactive = "Y"
+  )
+  expect_type(volcano_test, "list")
+  expect_true("plotly" %in% class(volcano_test))
+  expect_equal(volcano_test$height, 700)
+  expect_equal(volcano_test$width, 800)
+})
diff --git a/tests/testthat/test-dataset_merge.R b/tests/testthat/test-dataset_merge.R
new file mode 100644
index 0000000..020a258
--- /dev/null
+++ b/tests/testthat/test-dataset_merge.R
@@ -0,0 +1,54 @@
+df1 <- iris |>
+  dplyr::select(Species) |>
+  dplyr::distinct()
+
+df2 <- iris |>
+  dplyr::select(Species, dplyr::ends_with("Width"))
+
+test_that("dataset_merge works", {
+  expected <- dplyr::left_join(df1, df2, by = "Species")
+  actual <- dataset_merge(df1, df2, byvars = "Species")
+  expect_identical(expected, actual)
+})
+
+test_that("dataset_merge works with subsets and for > 2 datasets to merge", {
+  df12 <- dplyr::filter(df1, Species == "setosa")
+  df21 <- dplyr::filter(df2, Sepal.Width > 3)
+  df13 <- dplyr::filter(df1, Species != "versicolor")
+  expected1 <- dplyr::left_join(df1, df21, by = "Species")
+  actual1 <-
+    dataset_merge(df1, df2, byvars = "Species", subset = list(NA_character_, "Sepal.Width > 3"))
+  expected2 <- dplyr::left_join(df12, df21, by = "Species")
+  actual2 <-
+    dataset_merge(df1, df2, byvars = "Species", subset = list("Species == 'setosa'", "Sepal.Width > 3")) # nolint
+  expected3 <- purrr::reduce(list(df13, df12, df2), dplyr::left_join, "Species")
+  actual3 <-
+    dataset_merge(
+      df1, df1, df2,
+      byvars = "Species",
+      subset = list("Species != 'versicolor'", "Species == 'setosa'", NA_character_)
+    )
+  expect_identical(expected1, actual1)
+  expect_identical(expected2, actual2)
+  expect_identical(expected3, actual3)
+})
+
+test_that("dataset_merge returns expected errors", {
+  expect_error(
+    dataset_merge(
+      df1,
+      df2,
+      byvars = "xxx"
+    ),
+    "`byvars` not present"
+  )
+  expect_error(
+    dataset_merge(
+      df1,
+      df2,
+      byvars = "Species",
+      subset = list(NA_character_, NA_character_)
+    ),
+    "All subsets cannot be `NA`, use `subset = NULL` instead"
+  )
+})
diff --git a/tests/testthat/test-forest_plot.R b/tests/testthat/test-forest_plot.R
index 71dbbb3..6ded5ca 100644
--- a/tests/testthat/test-forest_plot.R
+++ b/tests/testthat/test-forest_plot.R
@@ -1,138 +1,133 @@
-data(ae_pre)
-
-risk_dat <- risk_stat(
-  datain = ae_pre$dsin,
-  d_datain = ae_pre$dout,
-  summary_by = "Patients",
-  eventVar = "AEDECOD",
-  ctrlgrp = "Placebo",
-  trtgrp = "Xanomeline High Dose~~Xanomeline Low Dose",
-  statistics = "Risk Ratio",
-  alpha = 0.05,
-  cutoff = 5,
-  sort_opt = "Ascending",
-  sort_var = "Count"
-)
-risk_dat1 <- risk_stat(
-  datain = ae_pre$dsin,
-  d_datain = ae_pre$dout,
-  summary_by = "Events",
-  eventVar = "AEBODSYS",
-  ctrlgrp = "Placebo",
-  trtgrp = "Xanomeline High Dose~~Xanomeline Low Dose",
-  statistics = "Risk Difference",
-  alpha = 0.05,
-  cutoff = 5,
-  sort_opt = "Ascending",
-  sort_var = "Count"
+data("ae_risk")
+options(warn = -1)
+fp <- forest_plot_base(
+  ae_risk,
+  xvar = "RISK",
+  yvar = "DPTVAL",
+  xminvar = "RISKCIL",
+  xmaxvar = "RISKCIU",
+  hovervar = "HOVER_RISK",
+  series_var = "TRTPAIR",
+  xrefline = 1,
+  hline_y = "Y",
+  axis_opts = plot_axis_opts(
+    xaxis_label = "Risk Ratio",
+    xopts = list(labelsize = 8)
+  ),
+  legend_opts = list(pos = "bottom", dir = "horizontal")
 )
-
-test_that("Forest Plot Works with standard inputs", {
-  fp_out <- forest_plot(
-    datain = risk_dat,
-    AE_Filter = "Any",
-    review_by = c("AEBODSYS", "AEDECOD"),
-    summary_by = "Patients",
-    statistics = "Risk Ratio",
-    xref = 1,
-    pvalcut = 0.05,
-    trtbign = "Y",
-    scale_trans = "identity"
-  )
-  # Check that expected 6 outputs are returned:
-  expect_equal(names(fp_out), c("ptly", "plot", "drill_plt", "rpt_data", "n", "title", "footnote"))
-
-  # Check type of plotly object returned
-  expect_true(fp_out$ptly$x$subplot)
-  # Check that the event variable selected (label) is correct:
-  expect_equal(
-    fp_out$ptly$x$layout$xaxis$title$text,
-    "AE Dictionary-Derived Term"
-  )
-  # Check the chosen statistic as label
-  expect_equal(
-    fp_out$ptly$x$layout$xaxis3$title$text,
-    "Risk Ratio"
-  )
-  # Check title and footnote
-  expect_equal(fp_out$title, "Forest plot for Risk Ratio of Any Adverse Events")
-
-  expect_equal(
-    fp_out$footnote,
-    paste0(
-      "* N is the total number of participants. \nClassifications of adverse ",
-      "events are based on the Medical Dictionary for Regulatory Activities (MedDRA v21.1",
-      "). \nDashed Vertical line represents risk value reference line. \nTotals for the ",
-      "No. of Participants/Events at a higher level are not necessarily the sum of those ",
-      "at the lower levels since a participant may report two or more. \nThe number of ",
-      "participants reporting at least 1 occurrence of the event specified."
+test_that("Test case 1: Forest Plot Base Works with standard inputs", {
+  expect_true(is.ggplot(fp))
+  expect_equal(fp[["data"]], ae_risk)
+  purrr::walk(c("mapping", "layers", "theme"), \(x) expect_snapshot(fp[[x]]))
+  expect_error(forest_plot_base(
+    datain = data.frame(),
+    xvar = "RISK",
+    yvar = "DPTVAL",
+    xminvar = "RISKCIL",
+    xmaxvar = "RISKCIU",
+    hovervar = "HOVER_RISK",
+    series_var = "TRTPAIR",
+    xrefline = 1,
+    hline_y = "N",
+    axis_opts = plot_axis_opts(
+      xaxis_label = "Risk Ratio",
+      xopts = list(labelsize = 8)
     )
-  )
-  # Graph data is from input data:
-  expect_type(fp_out$rpt_data, "list")
-  expect_true(nrow(fp_out$rpt_data) <= nrow(risk_dat))
+  ))
 })
 
-test_that("Forest plot arguments reflect correctly", {
-  fp_out1 <- forest_plot(
-    datain = risk_dat1,
-    AE_Filter = NULL,
-    review_by = "AEBODSYS",
-    summary_by = "Events",
-    statistics = "Risk Difference",
-    trtbign = "N",
-    scale_trans = "log10"
+# Forest Scatter plot
+sp <-
+  forest_plot_scatter(
+    datain = ae_risk,
+    xvar = "PCT",
+    yvar = "DPTVAL",
+    series_var = "TRTVAR",
+    series_opts = list(
+      color = g_seriescol(ae_risk, c("black", "goldenrod"), "TRTVAR"),
+      shape = g_seriessym(ae_risk, NA, "TRTVAR"),
+      size = rep(1, 2)
+    ),
+    hovervar = "HOVER_PCT",
+    xaxis_pos = "top",
+    legend_opts = list(pos = "bottom", dir = "horizontal"),
+    hline_y = "Y",
+    axis_opts = list(xsize = 8, xtsize = 4, xaxis_label = "Percentage")
   )
+test_that("Test case 1: Forest Plot Scatter Works with standard inputs", {
+  expect_true(is.ggplot(sp))
+  expect_equal(sp[["data"]], ae_risk)
+  purrr::walk(c("mapping", "layers", "theme"), \(x) expect_snapshot(sp[[x]]))
+})
 
-  # Review term reflects in legend
-  expect_equal(
-    fp_out1$ptly$x$layout$xaxis$title$text,
-    "Body System or Organ Class"
+test_that("Test Case 2: Forest plot scatter errors resolve correctly", {
+  expect_error(
+    forest_plot_scatter(
+      datain = data.frame(),
+      xvar = "PCT",
+      yvar = "DPTVAL",
+      series_var = "TRTVAR",
+      series_opts = list(
+        color = g_seriescol(ae_risk, c("black", "goldenrod"), "TRTVAR"),
+        shape = g_seriessym(ae_risk, NA, "TRTVAR"),
+        size = rep(1, 2)
+      ),
+      hovervar = "HOVER_PCT",
+      xaxis_pos = "top",
+      hline_y = "N",
+      axis_opts = list(xsize = 8, xtsize = 6, xaxis_label = "Percentage")
+    )
   )
+})
 
-  # Treatment legend does not contain (N = count)
-  legendtext <- unlist(purrr::map(
-    seq_along(fp_out1$ptly$x$data),
-    function(i) fp_out1$ptly$x$data[[i]]$name
-  ))
-  expect_false(any(str_detect(legendtext[1:3], "\\(N=")))
-  expect_equal(legendtext[1:3], unique(risk_dat1$TRTVAR))
-
-  # Check the chosen statistic as label
-  expect_equal(
-    fp_out1$ptly$x$layout$xaxis3$title$text,
-    "Risk Difference"
+tt <- ae_risk |>
+  mutate(XVAR = "HT") |>
+  tbl_to_plot(
+    yvar = "DPTVAL",
+    labelvar = "DPTVAL",
+    text_size = 2,
+    axis_opts = list(xaxis_label = "", xsize = 8, xtsize = 0)
+  ) +
+  theme(axis.text.x = element_blank())
+test_that("Test Case 1: forest_display static works correctly", {
+  actual <- forest_display(
+    plot_list = list(splot = sp, fplot = fp),
+    rel_widths = c(0.6, 0.4),
+    interactive = "N"
   )
-  # Check title and footnote
-  expect_equal(fp_out1$title, "Forest plot for Risk Difference of  Adverse Events")
-
-  expect_equal(
-    fp_out1$footnote,
-    paste0(
-      "* N is the total number of events. \nClassifications of adverse events are ",
-      "based on the Medical Dictionary for Regulatory Activities (MedDRA v21.1). ",
-      "\nDashed Vertical line represents risk value reference line. \nTotals for ",
-      "the No. of Participants/Events at a higher level are not necessarily the ",
-      "sum of those at the lower levels since a participant may report two or more.",
-      " \nEvent counts are the sum of individual occurrences within that category."
+  expect_type(actual, "list")
+  expect_true("ggplot" %in% class(actual))
+  expect_true("waiver" %in% class(actual$data))
+  expect_length(actual$layers, 3)
+  expect_error(
+    forest_display(
+      plot_list = list(sp = sp, fp = fp),
+      rel_widths = c(0.6, 0.4),
+      interactive = "N"
     )
   )
+  expect_error(
+    forest_display(
+      plot_list = list(splot = sp, fplot = fp),
+      rel_widths = c(0.6),
+      interactive = "N"
+    ),
+    "rel_widths should be equal to the number of plot columns"
+  )
 })
-## Test with empty data
-test_that("Forest Plot works as expected with empty `risk_stat()` output", {
-  risk_stat_null <- tibble()
-  fp_null <- forest_plot(
-    datain = risk_stat_null,
-    AE_Filter = "Any",
-    review_by = c("AEBODSYS", "AEDECOD"),
-    summary_by = "Patients",
-    statistics = "Risk Ratio",
-    xref = 1,
-    pvalcut = 0.05,
-    trtbign = "Y",
-    scale_trans = "identity"
+
+test_that("Test Case 1: forest_display interactive works correctly", {
+  actual <- forest_display(
+    plot_list = list(termtable = tt, splot = sp, fplot = fp),
+    rel_widths = c(0.25, 0.38, 0.27),
+    interactive = "Y",
+    plot_height = 800,
+    xpos = "top"
   )
-  expect_equal(length(fp_null), 3)
-  expect_equal(names(fp_null), c("ptly", "plot", "rpt_data"))
-  expect_identical(risk_stat_null, fp_null$rpt_data)
+  expect_type(actual, "list")
+  expect_true("plotly" %in% class(actual))
+  expect_true(actual$x$subplot)
+  expect_equal(actual$height, 800)
+  expect_snapshot(actual$x$layout)
 })
diff --git a/tests/testthat/test-mcatstat.R b/tests/testthat/test-mcatstat.R
index b3826e4..21f58ed 100644
--- a/tests/testthat/test-mcatstat.R
+++ b/tests/testthat/test-mcatstat.R
@@ -1,194 +1,204 @@
-data(adsl)
-data(ae_pre)
-
-# Sample Input 1
-ad_entry <- mentry(
-  datain = adsl,
-  ui_aSubset = NA,
-  ui_dSubset = "USUBJID!=''",
-  ui_byvar = NA,
-  ui_subgrpvar = NA,
-  ui_trtvar = "TRT01A",
-  ui_trtsort = "TRT01AN",
-  ui_addGrpMiss = "N",
-  ui_pop_fil = NA
-)
+data("adsl")
+data("ae_pre_process")
+ae_entry <-
+  ae_pre_process$data |> mentry(
+    subset = NA,
+    byvar = "AEBODSYS",
+    trtvar = "TRTA",
+    trtsort = "TRTAN",
+    subgrpvar = NA,
+    trttotalyn = "N",
+    add_grpmiss = "N",
+    sgtotalyn = "N",
+    pop_fil = "SAFFL"
+  )
+ad_entry <-
+  adsl |> mentry(
+    subset = "EFFFL=='Y'",
+    trtvar = "TRT01A",
+    trtsort = "TRT01AN",
+    trttotalyn = "N",
+    add_grpmiss = "N",
+    sgtotalyn = "N",
+    pop_fil = NA
+  )
 
 # Sample Output created from defaults
-ad_sum <- ad_entry$dsin %>%
-  group_by(TRTVAR, SEX) %>%
-  summarise(FREQ = n_distinct(USUBJID)) %>%
-  ungroup() %>%
-  group_by(TRTVAR) %>%
+ad_sum <- ad_entry |>
+  group_by(across(all_of(c("TRTVAR", "SEX")))) |>
+  summarise(FREQ = length(unique(.data[["USUBJID"]]))) |>
+  ungroup() |>
+  group_by(across(all_of("TRTVAR"))) |>
   mutate(
-    DPTVAL = as.character(SEX), DENOMN = sum(FREQ),
-    PCT = format(round(100 * FREQ / DENOMN, 2), nsmall = 2),
-    CVALUE = paste0(FREQ, " (", PCT, "%)"), CN = "C",
-    DPTVARN = 1, XVAR = DPTVAL,
-    DPTVAR = "SEX"
-  ) %>%
-  ungroup() %>%
-  select(-SEX) %>%
-  arrange(TRTVAR, DPTVAL)
-
-# sample input 2
-ad_entry1 <- mentry(
-  datain = adsl,
-  ui_aSubset = NA,
-  ui_dSubset = "USUBJID!=''",
-  ui_byvar = "RACE",
-  ui_subgrpvar = "ETHNIC",
-  ui_trtvar = "TRT01A",
-  ui_trtsort = "TRT01AN",
-  ui_addGrpMiss = "N",
-  ui_pop_fil = NA
-)
-
-
-test_that("Case 1:mcatstat output with standard inputs", {
+    DPTVAL = as.character(.data[["SEX"]]), DENOMN = sum(.data[["FREQ"]]),
+    PCT = round_f(100 * .data[["FREQ"]] / .data[["DENOMN"]], 2),
+    CVALUE = paste0(.data[["FREQ"]], " (", .data[["PCT"]], "%)"), CN = "C",
+    DPTVARN = 1, XVAR = .data[["DPTVAL"]],
+    DPTVAR = "SEX", DPTVALN = as.numeric(factor(.data[["SEX"]]))
+  ) |>
+  ungroup() |>
+  select(-all_of("SEX"))
+# Sample Cumulative output
+ad_cum <- ad_entry |>
+  group_by(across(all_of(c("TRTVAR", "SEX")))) |>
+  summarise(FREQ = length(unique(.data[["USUBJID"]]))) |>
+  mutate(DPTVAL = as.character(.data[["SEX"]]), FREQ = cumsum(.data[["FREQ"]])) |>
+  select(-all_of("SEX")) |>
+  ungroup()
+
+
+test_that("Case 1:mcatstat output with standard inputs and filters", {
   ad_mcat <- mcatstat(
-    datain = ad_entry$dsin,
-    d_datain = ad_entry$dout,
-    ui_dptvar = "SEX",
-    ui_pctdisp = "TRT"
+    datain = ad_entry,
+    uniqid = "USUBJID",
+    dptvar = "SEX",
+    pctdisp = "TRT"
   )
-
   # Check output returned is in expected format
   expect_type(ad_mcat, "list")
-  expect_identical(names(ad_mcat), c(
-    "DPTVAR", "DPTVAL", "XVAR", "TRTVAR",
-    "DENOMN", "DPTVALN", "FREQ", "PCT",
-    "CVALUE", "DPTVARN", "CN"
-  ))
-
+  expect_true(all(names(ad_mcat) %in% names(ad_sum)))
   # Check values are matched with expected:
-  expect_true(all_equal(ad_mcat %>% select(-DPTVALN), ad_sum))
+  expect_equal(ad_mcat, ad_sum |> select(all_of(names(ad_mcat))), ignore_attr = TRUE)
 })
 
 test_that("Case 2: Empty input", {
-  m_zero <- mcatstat(
-    datain = ad_entry$dsin %>% filter(USUBJID == "A"),
-    d_datain = ad_entry$dout,
-    ui_dptvar = "SEX",
-    ui_pctdisp = "TRT"
+  expect_error(
+    mcatstat(
+      datain = ad_entry |> filter(USUBJID == "A"),
+      dptvar = "SEX",
+      pctdisp = "TRT"
+    ),
+    "No data for mcatstat"
+  )
+  expect_error(
+    mcatstat(
+      datain = ad_entry,
+      uniqid = "XYZVAR",
+      dptvar = "SEX",
+      pctdisp = "TRT"
+    ),
+    "uniqid should exist in data or be ALLCT"
   )
-
-  expect_identical(m_zero, NULL)
 })
 
 
-test_that("Case 3: Unique ID variation", {
+test_that("Case 3: Unique ID and sign variation", {
   m_subj <- mcatstat(
-    datain = ae_pre$dsin,
-    d_datain = ae_pre$dout,
-    ui_uniqid = "USUBJID",
-    ui_dptvar = "AEDECOD",
-    ui_pctdisp = "TRT"
+    datain = ae_entry,
+    uniqid = "USUBJID",
+    dptvar = "AEDECOD",
+    pctdisp = "TRT",
+    pctsyn = "N"
   )
   m_na <- mcatstat(
-    datain = ae_pre$dsin,
-    d_datain = ae_pre$dout,
-    ui_uniqid = NA,
-    ui_dptvar = "AEDECOD",
-    ui_pctdisp = "TRT"
+    datain = ae_entry,
+    uniqid = "ALLCT",
+    dptvar = "AEDECOD",
+    pctdisp = "TRT",
+    pctsyn = "N"
   )
 
   # All groups and order except actual count values should be equal
   expect_equal(
-    m_subj %>% select(-c(DENOMN, FREQ, PCT, CVALUE)),
-    m_na %>% select(-c(DENOMN, FREQ, PCT, CVALUE))
+    m_subj |> select(-all_of(c("DENOMN", "FREQ", "PCT", "CVALUE"))),
+    m_na |> select(-all_of(c("DENOMN", "FREQ", "PCT", "CVALUE")))
   )
 
   # Counts are different
   expect_false(setequal(unique(m_subj$DENOMN), unique(m_na$DENOMN)))
 
   # Check values (for denominator, should also apply to numerator)
-  check_na <- ae_pre$dout %>%
-    ungroup() %>%
-    group_by(TRTVAR) %>%
-    summarise(DENOMN = n()) %>%
+  check_na <- ae_entry |>
+    ungroup() |>
+    group_by(TRTVAR) |>
+    summarise(DENOMN = n()) |>
     ungroup()
 
-  expect_equal(m_na %>% distinct(TRTVAR, DENOMN), check_na)
+  expect_equal(m_na |> distinct(across(all_of(c("TRTVAR", "DENOMN")))),
+    check_na,
+    ignore_attr = TRUE
+  )
+  expect_false(any(grep("%", m_subj$CVALUE)))
 })
 
-test_that("Case 4: Percentage denominator variation", {
-  # Invalid value for ui_pctdisp:
-  expect_null(mcatstat(
-    datain = ad_entry1$dsin,
-    d_datain = ad_entry1$dout,
-    ui_dptvar = "SEX",
-    ui_pctdisp = "ABC"
-  ))
+test_that("Case 4: Percentage denominator variation and denomyn", {
+  # Invalid value for pctdisp:
+  expect_error(mcatstat(
+    datain = ad_entry,
+    dptvar = "SEX",
+    pctdisp = "ABC"
+  ), "Invalid pctdisp")
 
   m_none <- mcatstat(
-    datain = ad_entry1$dsin,
-    d_datain = ad_entry1$dout,
-    ui_dptvar = "SEX",
-    ui_pctdisp = "NONE"
+    datain = ad_entry,
+    dptvar = "SEX",
+    pctdisp = "NONE"
   )
 
-
   # No percentage columns:
-  expect_identical(names(m_none), c(
-    "DPTVAR", "DPTVAL", "XVAR", "TRTVAR",
-    "SUBGRPVAR1", "SUBGRPVAR1N", "BYVAR1",
-    "BYVAR1N", "DPTVALN", "FREQ",
-    "CVALUE", "DPTVARN", "CN"
-  ))
+  expect_false(any(c("PCT", "DENOMN") %in% names(m_none)))
   expect_equal(m_none$FREQ, m_none$CVALUE)
 
   # Variable total as denominator
   m_var <- mcatstat(
-    datain = ad_entry1$dsin,
-    d_datain = ad_entry1$dout,
-    ui_dptvar = "SEX",
-    ui_pctdisp = "VAR"
+    datain = ad_entry,
+    dptvar = "SEX",
+    pctdisp = "VAR",
+    denomyn = "Y"
   )
-
   # Entire matrix has same denominator - check value
   expect_length(unique(m_var$DENOMN), 1)
-  expect_equal(unique(m_var$DENOMN), length(unique(ad_entry1$dout$USUBJID)))
+  expect_equal(unique(m_var$DENOMN), length(unique(ad_entry$USUBJID)))
+  expect_true(all(str_detect(m_var$CVALUE, paste0("/", unique(m_var$DENOMN)))))
 })
 
-test_that("Case 5: Cumulative Frequency", {
+test_that("Case 5: Cumulative Frequency and Total", {
   m_cum <- mcatstat(
-    datain = ad_entry$dsin,
-    d_datain = ad_entry$dout,
-    ui_dptvar = "SEX",
-    ui_pctdisp = "NO",
+    datain = ad_entry,
+    dptvar = "SEX",
+    pctdisp = "NO",
     cum_ctyn = "Y"
   )
-  ad_cum <- ad_entry$dsin %>%
-    group_by(TRTVAR, SEX) %>%
-    summarise(FREQ = n_distinct(USUBJID)) %>%
-    mutate(DPTVAL = as.character(SEX), FREQ = cumsum(FREQ)) %>%
-    select(-SEX) %>%
-    ungroup()
-
-  expect_equal(m_cum %>% select(TRTVAR, FREQ, DPTVAL), ad_cum)
-})
-
+  expect_equal(m_cum[, c("TRTVAR", "FREQ", "DPTVAL")], ad_cum)
 
-test_that("Case 6: Total category count", {
   m_total <- mcatstat(
-    datain = ad_entry$dsin,
-    d_datain = ad_entry$dout,
-    ui_dptvar = "SEX",
-    ui_pctdisp = "TRT",
+    datain = ad_entry,
+    dptvar = "SEX",
+    pctdisp = "TRT",
     total_catyn = "Y",
     cum_ctyn = "N"
   )
-
   expect_true("Total" %in% unique(m_total$DPTVAL))
   # Test single group
-  m_pl1 <- ad_sum %>%
-    filter(TRTVAR == "Placebo") %>%
-    select(FREQ) %>%
+  m_pl1 <- ad_sum |>
+    filter(.data[["TRTVAR"]] == "Placebo") |>
+    select(FREQ) |>
     sum()
-  m_pl2 <- m_total %>%
-    filter(TRTVAR == "Placebo", DPTVAL == "Total") %>%
+  m_pl2 <- m_total |>
+    filter(.data[["TRTVAR"]] == "Placebo", .data[["DPTVAL"]] == "Total") |>
     pull(FREQ)
+  expect_equal(m_pl2, m_pl1)
+})
 
-  expect_identical(m_pl2, m_pl1)
+test_that("Case 6: Filters check", {
+  m_num <- mcatstat(
+    datain = ad_entry,
+    a_subset = "SEX == 'F'",
+    uniqid = "USUBJID",
+    dptvar = "SEX",
+    pctdisp = "TRT"
+  )
+  m_denom <- mcatstat(
+    datain = ad_entry,
+    denom_subset = "SEX == 'F'",
+    uniqid = "USUBJID",
+    dptvar = "SEX",
+    pctdisp = "VAR"
+  )
+  expect_equal(unique(m_num$DPTVAL), "F")
+  denomvalue <- ad_entry |>
+    filter(.data[["SEX"]] == "F") |>
+    distinct(USUBJID) |>
+    nrow()
+  expect_equal(unique(m_denom$DENOMN), denomvalue)
 })
diff --git a/tests/testthat/test-mdisplay.R b/tests/testthat/test-mdisplay.R
deleted file mode 100644
index 55a59d8..0000000
--- a/tests/testthat/test-mdisplay.R
+++ /dev/null
@@ -1,148 +0,0 @@
-# test case-1
-data("ae_pre")
-# mcatstat output will the input for mdisplay
-mout <- mcatstat(
-  datain = ae_pre$dsin,
-  d_datain = ae_pre$dout,
-  ui_uniqid = "USUBJID",
-  ui_dptvar = "AEDECOD",
-  ui_pctdisp = "TRT",
-  miss_catyn = "N",
-  cum_ctyn = "N",
-  total_catyn = "N",
-  dptvarn = 1
-)
-# test case 1
-test_that("Test Case 1", {
-  actual <- mdisplay(
-    datain = mout,
-    ui_bylabel = NA,
-    ui_catlabel = NA,
-    ui_statlabel = NA,
-    trtbign = NA,
-    extra_df = NULL,
-    extra_mergeby = "DPTVAL",
-    extra_vars = "",
-    colformat = "",
-    indent = NULL,
-    dptlabel = "  "
-  )
-
-  BYVAR <- var_start(mout, "BYVAR")
-  BYVARN <- var_start(mout, "BYVARN")
-  report <- mout %>%
-    select(DPTVAR, TRTVAR, BYVAR, BYVARN, DPTVARN, DPTVALN, DPTVAL, CVALUE, CN) %>%
-    mutate(CVALUE = as.character(CVALUE))
-  rep <- report %>%
-    arrange(across(c("TRTVAR"))) %>%
-    tidyr::pivot_wider(
-      names_from = TRTVAR,
-      values_from = CVALUE,
-      values_fill = "-",
-      names_sort = FALSE
-    ) %>%
-    ungroup() %>%
-    mutate(across(!BYVAR & !DPTVAR & !DPTVAL & where(is.character), function(x) {
-      ifelse(CN == "C", gsub("-", "0", x), x)
-    }))
-  rep <- rep %>% select(BYVAR, DPTVAR, DPTVAL, everything())
-  repdat <- rep %>%
-    arrange(across(any_of(c(BYVARN, "DPTVARN", "DPTVALN")))) %>%
-    select(-any_of(BYVARN))
-
-  expect_equal(actual$dataf, repdat)
-})
-
-# test case 2
-test_that("Test Case 2", {
-  actual <- mdisplay(
-    datain = mout,
-    ui_bylabel = "SOC",
-    ui_catlabel = "VALUE",
-    ui_statlabel = NA,
-    trtbign = NA,
-    extra_df = NULL,
-    extra_mergeby = "DPTVAL",
-    extra_vars = "",
-    colformat = "",
-    indent = NULL,
-    dptlabel = "  "
-  )
-
-  BYVAR <- var_start(mout, "BYVAR")
-  BYVARN <- var_start(mout, "BYVARN")
-  report <- mout %>%
-    select(DPTVAR, TRTVAR, BYVAR, BYVARN, DPTVARN, DPTVALN, DPTVAL, CVALUE, CN) %>%
-    mutate(CVALUE = as.character(CVALUE))
-  rep <- report %>%
-    arrange(across(c("TRTVAR"))) %>%
-    tidyr::pivot_wider(
-      names_from = TRTVAR,
-      values_from = CVALUE,
-      values_fill = "-",
-      names_sort = FALSE
-    ) %>%
-    ungroup() %>%
-    mutate(across(!BYVAR & !DPTVAR & !DPTVAL & where(is.character), function(x) {
-      ifelse(CN == "C", gsub("-", "0", x), x)
-    }))
-  rep <- rep %>% select(BYVAR, DPTVAR, DPTVAL, everything())
-  repdat <- rep %>%
-    arrange(across(any_of(c(BYVARN, "DPTVARN", "DPTVALN")))) %>%
-    select(-any_of(BYVARN)) %>%
-    rename("SOC" = BYVAR) %>%
-    mutate(DPTVAR = "VALUE")
-
-  expect_equal(actual$dataf, repdat)
-})
-
-# test case 3
-test_that("Test Case 3", {
-  actual <- mdisplay(
-    datain = mout,
-    ui_bylabel = "SOC",
-    ui_catlabel = "VALUE",
-    ui_statlabel = NA,
-    trtbign = ae_pre$bigN,
-    extra_df = NULL,
-    extra_mergeby = "DPTVAL",
-    extra_vars = "",
-    colformat = " ",
-    indent = "DPTVALN == 1",
-    dptlabel = "  "
-  )
-
-  BYVAR <- var_start(mout, "BYVAR")
-  BYVARN <- var_start(mout, "BYVARN")
-  report <- mout %>%
-    select(DPTVAR, TRTVAR, BYVAR, BYVARN, DPTVARN, DPTVALN, DPTVAL, CVALUE, CN) %>%
-    mutate(CVALUE = as.character(CVALUE))
-  rep <- report %>%
-    arrange(across(c("TRTVAR"))) %>%
-    tidyr::pivot_wider(
-      names_from = TRTVAR,
-      values_from = CVALUE,
-      values_fill = "-",
-      names_sort = FALSE
-    ) %>%
-    ungroup() %>%
-    mutate(across(!BYVAR & !DPTVAR & !DPTVAL & where(is.character), function(x) {
-      ifelse(CN == "C", gsub("-", "0", x), x)
-    }))
-  rep <- rep %>% select(BYVAR, DPTVAR, DPTVAL, everything())
-  report <- rep %>%
-    arrange(across(any_of(c(BYVARN, "DPTVARN", "DPTVALN")))) %>%
-    select(-any_of(BYVARN)) %>%
-    rename("SOC" = BYVAR) %>%
-    mutate(DPTVAR = "VALUE")
-  trtbign <- ae_pre$bigN
-  n <- paste0("Placebo (N = ", trtbign$BIGN[1], ")")
-  repdat <- report %>% rename(
-    !!paste0("Placebo (N=", trtbign$BIGN[1], ")", " ") := "Placebo",
-    !!paste0("Xanomeline Low Dose (N=", trtbign$BIGN[2], ")", " ") := "Xanomeline Low Dose",
-    !!paste0("Xanomeline High Dose (N=", trtbign$BIGN[3], ")", " ") := "Xanomeline High Dose",
-    !!paste0("Total (N=", trtbign$BIGN[4], ")", " ") := "Total"
-  )
-
-  expect_equal(actual$dataf, repdat)
-})
diff --git a/tests/testthat/test-risk_stat.R b/tests/testthat/test-risk_stat.R
index 2608a8e..723380b 100644
--- a/tests/testthat/test-risk_stat.R
+++ b/tests/testthat/test-risk_stat.R
@@ -1,53 +1,58 @@
-data(ae_pre)
-dsin <- ae_pre$dsin
-dout <- ae_pre$dout
-
+data("ae_pre_process")
+ae_entry <- mentry(
+  datain = ae_pre_process$data,
+  subset = NA,
+  byvar = "AEBODSYS",
+  trtvar = "TRTA",
+  trtsort = "TRTAN",
+  subgrpvar = NA,
+  trttotalyn = "N",
+  add_grpmiss = "N",
+  sgtotalyn = "N",
+  pop_fil = "SAFFL"
+)
+dsin1 <- ae_entry |>
+  filter(AEDECOD %in% c("NAUSEA", "SINUS BRADYCARDIA"))
+
+denom <- dsin1 |>
+  filter(TRTVAR %in% c("Placebo", "Xanomeline High Dose")) |>
+  group_by(TRTVAR) |>
+  summarise(N = length(unique(USUBJID))) |>
+  ungroup()
+
+freq <- dsin1 |>
+  filter(TRTVAR %in% c("Placebo", "Xanomeline High Dose") &
+    eval(parse(text = ae_pre_process$a_subset))) |>
+  group_by(TRTVAR, AEBODSYS, AEDECOD) |>
+  summarise(n = length(unique(USUBJID))) |>
+  ungroup()
+
+exp <- left_join(denom, freq, by = "TRTVAR")
+
+idvar <- c("AEBODSYS", "AEDECOD")
+exp1 <- exp |>
+  mutate(TRTVAR = case_when(
+    TRTVAR == "Placebo" ~ "ctrlgrp",
+    TRTVAR == "Xanomeline High Dose" ~ "trtgrp"
+  )) |>
+  tidyr::pivot_wider(id_cols = any_of(c(idvar)), names_from = TRTVAR, values_from = c(N, n)) |>
+  mutate(
+    temp1 = N_ctrlgrp - n_ctrlgrp,
+    temp2 = N_trtgrp - n_trtgrp
+  )
+mat <- matrix(c(2, 7, 3, 6), nrow = 2)
 # testcase 1
 
 test_that("Test Case 1: Check if the function gives expected statistic values", {
-  dsin1 <- dsin %>%
-    filter(AEDECOD %in% c("NAUSEA", "SINUS BRADYCARDIA")) %>%
-    select(USUBJID, TRTA, AEDECOD, AEBODSYS, TRTVAR, BYVAR1)
-  dout1 <- dout %>%
-    filter(AEDECOD %in% c("NAUSEA", "SINUS BRADYCARDIA")) %>%
-    select(USUBJID, TRTA, AEDECOD, AEBODSYS, TRTVAR, BYVAR1)
-
-  denom <- dsin1 %>%
-    filter(TRTVAR %in% c("Placebo", "Xanomeline High Dose")) %>%
-    group_by(TRTVAR) %>%
-    summarise(N = length(unique(USUBJID))) %>%
-    ungroup()
-
-  freq <- dsin1 %>%
-    filter(TRTVAR %in% c("Placebo", "Xanomeline High Dose")) %>%
-    group_by(TRTVAR, AEBODSYS, AEDECOD) %>%
-    summarise(n = length(unique(USUBJID))) %>%
-    ungroup()
-
-  exp <- left_join(denom, freq, by = "TRTVAR")
-
-  idvar <- c("AEBODSYS", "AEDECOD")
-  exp1 <- exp %>%
-    mutate(TRTVAR = case_when(
-      TRTVAR == "Placebo" ~ "ctrlgrp",
-      TRTVAR == "Xanomeline High Dose" ~ "trtgrp"
-    )) %>%
-    tidyr::pivot_wider(id_cols = any_of(c(idvar)), names_from = TRTVAR, values_from = c(N, n)) %>%
-    mutate(
-      temp1 = N_ctrlgrp - n_ctrlgrp,
-      temp2 = N_trtgrp - n_trtgrp
-    )
-
-  mat <- matrix(c(2, 7, 3, 6), nrow = 2)
-  risk <- riskratio.wald(mat, conf.level = 1 - 0.05)
+  risk <- suppressWarnings(epitools::riskratio.wald(mat, conf.level = 1 - 0.05))
 
   risk_val <- round(risk$measure[2, 1], 3)
   pval <- round(risk$p.value[2, 3], 4)
   cil <- round(risk$measure[2, 2], 2)
   ciu <- round(risk$measure[2, 3], 2)
 
-  expected <- exp %>%
-    filter(AEDECOD == "NAUSEA") %>%
+  expected <- exp |>
+    filter(AEDECOD == "NAUSEA") |>
     mutate(
       RISK = risk_val,
       PVALUE = pval,
@@ -59,9 +64,9 @@ test_that("Test Case 1: Check if the function gives expected statistic values",
 
   risk_s <- risk_stat(
     datain = dsin1,
-    d_datain = dout1,
+    a_subset = ae_pre_process$a_subset,
     summary_by = "Patients",
-    eventVar = "AEDECOD",
+    eventvar = "AEDECOD",
     ctrlgrp = "Placebo",
     trtgrp = "Xanomeline High Dose",
     statistics = "Risk Ratio",
@@ -71,97 +76,121 @@ test_that("Test Case 1: Check if the function gives expected statistic values",
     sort_var = "Count"
   )
 
-  actual <- risk_s %>%
-    rename(AEBODSYS = BYVAR1, AEDECOD = DPTVAL, N = TOTAL_N, n = FREQ) %>%
-    filter(AEDECOD == "NAUSEA") %>%
+  actual <- risk_s |>
+    rename(AEBODSYS = BYVAR1, AEDECOD = DPTVAL, N = TOTAL_N, n = FREQ) |>
+    filter(AEDECOD == "NAUSEA") |>
     mutate(
       N = as.integer(N),
       n = as.integer(n)
-    ) %>%
+    ) |>
     select(TRTVAR, N, AEBODSYS, AEDECOD, n, RISK, PVALUE, RISKCIL, RISKCIU, PCT)
 
   expect_equal(actual$RISK, expected$RISK)
   expect_equal(actual$PVALUE, expected$PVALUE)
-  expect_identical(actual, expected)
+  expect_equal(actual, expected, ignore_attr = TRUE)
 })
 
 # testcae 2
 
 test_that("Test Case 2: Check if the function works as expected for risk difference", {
-  dsin1 <- dsin %>%
-    filter(AEDECOD %in% c("NAUSEA", "SINUS BRADYCARDIA")) %>%
-    select(USUBJID, TRTA, AEDECOD, AEBODSYS, TRTVAR, BYVAR1)
-  dout1 <- dout %>%
-    filter(AEDECOD %in% c("NAUSEA", "SINUS BRADYCARDIA")) %>%
-    select(USUBJID, TRTA, AEDECOD, AEBODSYS, TRTVAR, BYVAR1)
-
-  denom <- dsin1 %>%
-    filter(TRTVAR %in% c("Placebo", "Xanomeline High Dose")) %>%
-    group_by(TRTVAR) %>%
-    summarise(N = length(unique(USUBJID))) %>%
-    ungroup()
-
-  freq <- dsin1 %>%
-    filter(TRTVAR %in% c("Placebo", "Xanomeline High Dose")) %>%
-    group_by(TRTVAR, AEBODSYS, AEDECOD) %>%
-    summarise(n = length(unique(USUBJID))) %>%
-    ungroup()
-
-  exp <- left_join(denom, freq, by = "TRTVAR")
-
-  idvar <- c("AEBODSYS", "AEDECOD")
-  exp1 <- exp %>%
-    mutate(TRTVAR = case_when(
-      TRTVAR == "Placebo" ~ "ctrlgrp",
-      TRTVAR == "Xanomeline High Dose" ~ "trtgrp"
-    )) %>%
-    tidyr::pivot_wider(id_cols = any_of(c(idvar)), names_from = TRTVAR, values_from = c(N, n)) %>%
-    mutate(
-      temp1 = N_ctrlgrp - n_ctrlgrp,
-      temp2 = N_trtgrp - n_trtgrp
-    )
-
-  mat <- matrix(c(2, 7, 3, 6), nrow = 2)
-  risk <- riskdiff_wald(mat, conf.level = 1 - 0.05)
+  risk <- suppressWarnings(riskdiff_wald(mat, conf.level = 1 - 0.05))
 
   risk_val <- round(risk$measure[2, 1], 3)
   pval <- round(risk$p.value[2, 3], 4)
   ciu <- round(risk$measure[2, 2], 4)
   cil <- round(risk$measure[2, 3], 4)
 
-  expected <- exp %>%
-    filter(AEDECOD == "NAUSEA") %>%
+  expected <- exp |>
+    filter(AEDECOD == "NAUSEA") |>
     mutate(
       RISK = risk_val,
       PVALUE = pval,
       TRTVAR = as.character(TRTVAR)
-    ) %>%
+    ) |>
     arrange(desc(RISK))
 
   risk_s <- risk_stat(
     datain = dsin1,
-    d_datain = dout1,
+    a_subset = ae_pre_process$a_subset,
     summary_by = "Patients",
-    eventVar = "AEDECOD",
+    eventvar = "AEDECOD",
     ctrlgrp = "Placebo",
     trtgrp = "Xanomeline High Dose",
     statistics = "Risk Difference",
     alpha = 0.05,
-    cutoff = 2,
+    cutoff = 0,
     sort_opt = "Descending",
     sort_var = "RiskValue"
   )
 
-  actual <- risk_s %>%
-    rename(AEBODSYS = BYVAR1, AEDECOD = DPTVAL, N = TOTAL_N, n = FREQ) %>%
-    filter(AEDECOD == "NAUSEA") %>%
+  actual <- risk_s |>
+    rename(AEBODSYS = BYVAR1, AEDECOD = DPTVAL, N = TOTAL_N, n = FREQ) |>
+    filter(AEDECOD == "NAUSEA") |>
     mutate(
       N = as.integer(N),
       n = as.integer(n)
-    ) %>%
+    ) |>
     select(TRTVAR, N, AEBODSYS, AEDECOD, n, RISK, PVALUE)
 
   expect_equal(actual$RISK, expected$RISK)
   expect_equal(actual$PVALUE, expected$PVALUE)
+  expect_equal(actual, expected, ignore_attr = TRUE)
+})
+
+# test case 1
+
+test_that("riskdiff_wald: check if the function works as expected", {
+  evts <- 4
+  non_evts <- 6
+  control_evts <- 3
+  cne <- 8
+
+  expected_output <- (evts / (evts + non_evts)) - (control_evts / (control_evts + cne))
+  actual <- suppressWarnings(riskdiff_wald(matrix(c(evts, control_evts, non_evts, cne), nrow = 2)))
+  actual_output <- actual$measure[2, 1]
+
+  expect_equal(actual_output, expected_output, ignore_attr = TRUE)
+})
+
+# test case 2
+
+test_that("riskdiff_wald: check for error if `y` argument is not NULL", {
+  evts <- 4
+  non_evts <- 6
+  control_evts <- 3
+  cne <- 8
+  input <- matrix(c(evts, control_evts, non_evts, cne), nrow = 2)
+
+  expect_error(
+    suppressWarnings(
+      riskdiff_wald(
+        x = input,
+        y = 2,
+        conf.level = 0.95,
+        rev = c("neither", "rows", "columns", "both"),
+        correction = FALSE,
+        verbose = FALSE
+      )
+    ),
+    regexp = paste("y argument should be NULL")
+  )
+})
+
+test_that("risk_stat: returns empty data frame when cutoff is too high", {
+  actual <- risk_stat(
+    datain = ae_entry,
+    a_subset = ae_pre_process$a_subset,
+    summary_by = "Patients",
+    eventvar = "AEDECOD",
+    ctrlgrp = "Placebo",
+    trtgrp = "Xanomeline High Dose",
+    statistics = "Risk Ratio",
+    alpha = 0.05,
+    cutoff = 500,
+    sort_opt = "Ascending",
+    sort_var = "Count"
+  )
+
+  expected <- data.frame(NULL)
   expect_identical(actual, expected)
 })
diff --git a/tests/testthat/test-volcano_plot.R b/tests/testthat/test-volcano_plot.R
deleted file mode 100644
index c133a04..0000000
--- a/tests/testthat/test-volcano_plot.R
+++ /dev/null
@@ -1,113 +0,0 @@
-data(ae_pre)
-
-risk_stat_out <- risk_stat(
-  datain = ae_pre$dsin,
-  d_datain = ae_pre$dout,
-  summary_by = "Patients",
-  eventVar = "AEDECOD",
-  ctrlgrp = "Placebo",
-  trtgrp = "Xanomeline High Dose",
-  statistics = "Risk Ratio",
-  alpha = 0.05,
-  cutoff = 2,
-  sort_opt = "Ascending",
-  sort_var = "Count"
-)
-
-test_that("Test Case 1: volcano_plot works with expected inputs", {
-  vout <- volcano_plot(
-    datain = ae_pre,
-    AE_Filter = "Safety",
-    statistics_data = risk_stat_out,
-    statistics = "Risk Difference",
-    treatment1 = "Placebo",
-    treatment2 = "Xanomeline Low Dose",
-    X_ref = 1,
-    summary_by = "Patients",
-    pvalue_label = "None",
-    treatment1_label = "Control",
-    treatment2_label = "Exposure",
-    pvalcut = 0.05
-  )
-
-  ptly_data <- vout[["ptly"]][["x"]][["data"]]
-  legendgroups <-
-    unlist(purrr::compact(purrr::map(
-      seq_along(ptly_data),
-      function(x) ptly_data[[x]][["legendgroup"]]
-    )))
-
-  expect_equal(length(vout), 5)
-  expect_equal(names(vout), c("ptly", "plot", "rpt_data", "title", "footnote"))
-  expect_true(nrow(vout$rpt_data) > 0)
-  expect_type(vout$ptly, "list")
-  expect_equal(legendgroups, sort(unique(vout[["rpt_data"]][["BYVAR1"]])))
-  expect_identical(vout$plot$data, vout$rpt_data)
-  expect_equal(vout$title, "Volcano plot for Risk Difference of Safety Adverse Events")
-  expect_equal(vout$footnote, "* N is the total number of participants. \nClassifications of adverse events are based on the Medical Dictionary for Regulatory Activities (MedDRA v21.1). \nDashed horizontal line represents p-value of 0.05.\nDotted horizontal line represents FDR adjusted p-value of approximately 0.05 (when applicable). \nDashed Vertical line represents risk value reference line. \nTotals for the No. of Participants/Events at a higher level are not necessarily the sum of those at the lower levels since a participant may report two or more. \nThe number of participants reporting at least 1 occurrence of the event specified.") # nolint
-})
-
-
-test_that("Test Case 2: volcano_plot returns pre processed AE data with
-          empty `risk_stat()` output", {
-  risk_stat_out_ <- tibble()
-  vout <- volcano_plot(
-    datain = ae_pre,
-    AE_Filter = "Safety",
-    statistics_data = risk_stat_out_,
-    statistics = "Risk Difference",
-    treatment1 = "Placebo",
-    treatment2 = "Xanomeline Low Dose",
-    X_ref = 1,
-    summary_by = "Patients",
-    pvalue_label = "None",
-    treatment1_label = "Control",
-    treatment2_label = "Exposure",
-    pvalcut = 0.05
-  )
-
-  expect_equal(length(vout), 3)
-  expect_equal(names(vout), c("ptly", "plot", "rpt_data"))
-  expect_identical(ae_pre, vout$rpt_data)
-  expect_identical(ae_pre$dsin, vout$rpt_data$dsin)
-})
-
-
-test_that("Test Case 3: volcano_plot transforms p values correctly based on `pvalue_label`", {
-  vout_none <- volcano_plot(
-    datain = ae_pre,
-    AE_Filter = "Safety",
-    statistics_data = risk_stat_out,
-    statistics = "Risk Difference",
-    treatment1 = "Placebo",
-    treatment2 = "Xanomeline Low Dose",
-    X_ref = 1,
-    summary_by = "Patients",
-    pvalue_label = "None",
-    treatment1_label = "Control",
-    treatment2_label = "Exposure",
-    pvalcut = 0.05
-  )
-
-  vout_log <- volcano_plot(
-    datain = ae_pre,
-    AE_Filter = "Safety",
-    statistics_data = risk_stat_out,
-    statistics = "Risk Difference",
-    treatment1 = "Placebo",
-    treatment2 = "Xanomeline Low Dose",
-    X_ref = 1,
-    summary_by = "Patients",
-    pvalue_label = "-log10",
-    treatment1_label = "Control",
-    treatment2_label = "Exposure",
-    pvalcut = 0.05
-  )
-
-  expect_equal(length(vout_none), length(vout_log))
-  expect_equal(names(vout_none), names(vout_log))
-  expect_false(identical(
-    layer_scales(vout_log$plot)$y$break_positions(),
-    layer_scales(vout_none$plot)$y$break_positions()
-  ))
-})