diff --git a/R/ahr_blinded.R b/R/ahr_blinded.R
index 644167e4..691afe59 100644
--- a/R/ahr_blinded.R
+++ b/R/ahr_blinded.R
@@ -84,14 +84,14 @@ ahr_blinded <- function(
     hr = c(1, .6),
     ratio = 1) {
   # Input checking
-  if (!is.vector(hr, mode = "numeric") || min(hr) <= 0) {
-    stop("ahr_blinded: hr must be a vector of positive numbers.")
+  if (!is.numeric(hr) || min(hr) <= 0) {
+    stop("'hr' must be a vector of positive numbers.")
   }
-  if (!is.vector(intervals, mode = "numeric") || min(intervals) <= 0) {
-    stop("ahr_blinded: intervals must be a vector of positive numbers.")
+  if (!is.numeric(intervals) || min(intervals) <= 0) {
+    stop("'intervals' must be a vector of positive numbers.")
   }
   if (length(intervals) != length(hr)) {
-    stop("ahr_blinded: the piecewise model specified hr and intervals are not aligned.")
+    stop("the piecewise model specified 'hr' and 'intervals' differ in length.")
   }
 
   # Set final element of "intervals" to Inf
diff --git a/R/as_gt.R b/R/as_gt.R
index 59e0fe20..c31e3880 100644
--- a/R/as_gt.R
+++ b/R/as_gt.R
@@ -79,110 +79,57 @@ as_gt <- function(x, ...) {
 #'   summary() %>%
 #'   as_gt()
 as_gt.fixed_design <- function(x, title = NULL, footnote = NULL, ...) {
-  # get the design method
-  if ("ahr" %in% class(x)) {
-    design_mtd <- "ahr"
-  } else if ("fh" %in% class(x)) {
-    design_mtd <- "fh"
-  } else if ("mb" %in% class(x)) {
-    design_mtd <- "mb"
-  } else if ("lf" %in% class(x)) {
-    design_mtd <- "lf"
-  } else if ("rd" %in% class(x)) {
-    design_mtd <- "rd"
-  } else if ("maxcombo" %in% class(x)) {
-    design_mtd <- "maxcombo"
-  } else if ("milestone" %in% class(x)) {
-    design_mtd <- "milestone"
-  } else if ("rmst" %in% class(x)) {
-    design_mtd <- "rmst"
-  } else if ("rd" %in% class(x)) {
-    design_mtd <- "rd"
-  }
-
-
-  # set the default title
-  if (is.null(title)) {
-    title <- switch(design_mtd,
-      "ahr" = {
-        "Fixed Design under AHR Method"
-      },
-      "fh" = {
-        "Fixed Design under Fleming-Harrington Method"
-      },
-      "mb" = {
-        "Fixed Design under Magirr-Burman Method"
-      },
-      "lf" = {
-        "Fixed Design under Lachin and Foulkes Method"
-      },
-      "rd" = {
-        "Fixed Design of Risk Difference under Farrington-Manning Method"
-      },
-      "maxcombo" = {
-        "Fixed Design under MaxCombo Method"
-      },
-      "milestone" = {
-        "Fixed Design under Milestone Method"
-      },
-      "rmst" = {
-        "Fixed Design under Restricted Mean Survival Time Method"
-      },
-      "rd" = {
-        "Fixed Design of Risk Difference"
-      }
+  method <- fd_method(x)
+  ans <- gt::gt(x) %>%
+    gt::tab_header(title = title %||% fd_title(method)) %>%
+    gt::tab_footnote(
+      footnote = footnote %||% fd_footnote(x, method),
+      locations = gt::cells_title(group = "title")
     )
-  }
-
+  return(ans)
+}
 
-  # set the default footnote
-  if (is.null(footnote)) {
-    footnote <- switch(design_mtd,
-      "ahr" = {
-        "Power computed with average hazard ratio method."
-      },
-      "fh" = {
-        paste0(
-          "Power for Fleming-Harrington test ",
-          substr(x$Design, 19, nchar(x$Design)),
-          " using method of Yung and Liu."
-        )
-      },
-      "mb" = {
-        paste0(
-          "Power for ",
-          x$Design,
-          " computed with method of Yung and Liu."
-        )
-      },
-      "lf" = {
-        "Power using Lachin and Foulkes method applied
-        using expected average hazard ratio (AHR) at time of planned analysis."
-      },
-      "rd" = {
-        "Risk difference power without continuity correction using method of Farrington and Manning."
-      },
-      "maxcombo" = {
-        paste0(
-          "Power for MaxCombo test with Fleming-Harrington tests",
-          substr(x$Design, 9, nchar(x$Design)), "."
-        )
-      },
-      "milestone" = {
-        paste0("Power for ", x$Design, " computed with method of Yung and Liu.")
-      },
-      "rmst" = {
-        paste0("Power for ", x$Design, " computed with method of Yung and Liu.")
-      }
-    )
-  }
+# get the fixed design method
+fd_method <- function(x) {
+  methods <- c("ahr", "fh", "mb", "lf", "rd", "maxcombo", "milestone", "rmst")
+  intersect(methods, class(x))[1]
+}
 
-  ans <- x %>%
-    gt::gt() %>%
-    gt::tab_header(title = title) %>%
-    gt::tab_footnote(footnote = footnote, locations = gt::cells_title(group = "title"))
+# get the default title
+fd_title <- function(method) {
+  sprintf("Fixed Design %s Method", switch(
+    method,
+    ahr = "under AHR", fh = "under Fleming-Harrington", mb = "under Magirr-Burman",
+    lf = "under Lachin and Foulkes", maxcombo = "under MaxCombo",
+    milestone = "under Milestone", rmst = "under Restricted Mean Survival Time",
+    rd = "of Risk Difference under Farrington-Manning"
+  ))
+}
 
-  return(ans)
+# get the default footnote
+fd_footnote <- function(x, method) {
+  switch(
+    method,
+    ahr = "Power computed with average hazard ratio method.",
+    fh = paste(
+      "Power for Fleming-Harrington test", substring(x$Design, 19),
+      "using method of Yung and Liu."
+    ),
+    lf = paste(
+      "Power using Lachin and Foulkes method applied using expected",
+      "average hazard ratio (AHR) at time of planned analysis."
+    ),
+    rd = paste(
+      "Risk difference power without continuity correction using method of",
+      "Farrington and Manning."
+    ),
+    maxcombo = paste0(
+      "Power for MaxCombo test with Fleming-Harrington tests ",
+      substring(x$Design, 9), "."
+    ),
+    # for mb, milestone, and rmst
+    paste("Power for", x$Design, "computed with method of Yung and Liu.")
+  )
 }
 
 #' @rdname as_gt
@@ -303,259 +250,167 @@ as_gt.gs_design <- function(
     display_inf_bound = FALSE,
     ...) {
 
-  method <- class(x)[class(x) %in% c("ahr", "wlr", "combo", "rd")]
-  full_alpha <- attributes(x)$full_alpha
-
-  x_alpha <- max((x %>% dplyr::filter(Bound == display_bound[1]))[[colname_spannersub[2]]])
-
-  x_non_binding <- "non_binding" %in% class(x)
-
-  x_k <- lapply(x$Analysis, function(x) {
-    return(as.numeric(substring(x, 11, 11)))
-  }) %>% unlist()
-
-  if (!display_inf_bound) {
-    x <- x %>% filter(!is.infinite(Z))
-  }
-
   x_old <- x
+  full_alpha <- attr(x, "full_alpha")
+  parts <- gsd_parts(
+    x, title, subtitle, colname_spannersub, footnote,
+    display_bound, display_columns, display_inf_bound
+  )
 
-  # Set defaults ----
-  # set different default title to different methods
-  if (method == "ahr" && is.null(title)) {
-    title <- "Bound summary for AHR design"
-  }
-  if (method == "wlr" && is.null(title)) {
-    title <- "Bound summary for WLR design"
-  }
-  if (method == "combo" && is.null(title)) {
-    title <- "Bound summary for MaxCombo design"
-  }
+  x <- parts$x %>%
+    dplyr::group_by(Analysis) %>%
+    gt::gt() %>%
+    gt::tab_spanner(
+      columns = dplyr::all_of(colname_spannersub),
+      label = colname_spanner
+    ) %>%
+    gt::tab_header(title = parts$title, subtitle = parts$subtitle)
 
-  if (method == "rd" && is.null(title)) {
-    title <- "Bound summary of Binary Endpoint"
+  # Add footnotes ----
+  footnote <- parts$footnote
+  for (i in seq_along(footnote$content)) {
+    att <- footnote$attr[i]
+    loc <- if (att == "colname") {
+      # footnotes are added on the colnames
+      gt::cells_column_labels(columns = footnote$location[i])
+    } else if (att %in% c("title", "subtitle")) {
+      # on the title/subtitle
+      gt::cells_title(group = att)
+    } else if (att == "analysis") {
+      # on the analysis summary row, which is a grouping variable, i.e., Analysis
+      gt::cells_row_groups(groups = dplyr::starts_with("Analysis"))
+    } else if (att == "spanner") {
+      # on the column spanner
+      gt::cells_column_spanners(spanners = colname_spanner)
+    }
+    if (!is.null(loc))
+      x <- gt::tab_footnote(x, footnote = footnote$content[i], locations = loc)
   }
 
-  # set different default subtitle to different methods
-  if (method == "ahr" && is.null(subtitle)) {
-    subtitle <- "AHR approximations of ~HR at bound"
-  }
-  if (method == "wlr" && is.null(subtitle)) {
-    subtitle <- "WLR approximation of ~wHR at bound"
-  }
-  if (method == "combo" && is.null(subtitle)) {
-    subtitle <- "MaxCombo approximation"
-  }
-  if (method == "rd" && is.null(subtitle)) {
-    subtitle <- "measured by risk difference"
-  }
+  # add footnote for non-binding design
+  footnote_nb <- gsd_footnote_nb(x_old, parts$alpha, full_alpha)
+  if (!is.null(footnote_nb)) x <- gt::tab_footnote(
+    x,
+    footnote = footnote_nb,
+    locations = gt::cells_body(
+      columns = colname_spannersub[2],
+      rows = gsd_footnote_row(parts$x, display_bound[1])
+    )
+  )
 
+  return(x)
+}
+
+# get different default columns to display
+gsd_columns <- function(columns, method, x) {
   # set different default columns to display
-  if (is.null(display_columns)) {
-    if (method == "ahr") {
-      display_columns <- c(
-        "Analysis", "Bound", "Z", "Nominal p",
-        "~HR at bound", "Alternate hypothesis", "Null hypothesis"
-      )
-    } else if (method == "wlr") {
-      display_columns <- c(
-        "Analysis", "Bound", "Z", "Nominal p",
-        "~wHR at bound", "Alternate hypothesis", "Null hypothesis"
-      )
-    } else if (method == "combo") {
-      display_columns <- c(
-        "Analysis", "Bound", "Z", "Nominal p",
-        "Alternate hypothesis", "Null hypothesis"
-      )
-    } else if (method == "rd") {
-      display_columns <- c(
-        "Analysis", "Bound", "Z", "Nominal p",
-        "~Risk difference at bound", "Alternate hypothesis", "Null hypothesis"
-      )
-    }
-  }
-  # filter the columns to display as the output
-  ## if `Probability` is selected to output, then transform it to `c("Alternate hypothesis", "Null hypothesis")`
-  if ("Probability" %in% display_columns) {
-    display_columns <- display_columns[!display_columns == "Probability"]
-    display_columns <- c(display_columns, "Alternate hypothesis", "Null hypothesis")
-  }
+  if (is.null(columns)) columns <- c(
+    "Analysis", "Bound", "Z", "Nominal p",
+    sprintf("%s at bound", switch(method, ahr = "~HR", wlr = "~wHR", rd = "~Risk difference")),
+    "Alternate hypothesis", "Null hypothesis"
+  )
+  # filter the columns to display as the output: if `Probability` is selected to
+  # output, transform it to `c("Alternate hypothesis", "Null hypothesis")`
+  if (any(i <- columns == "Probability"))
+    columns <- c(columns[!i], "Alternate hypothesis", "Null hypothesis")
   ## check if the `display_columns` are included in `x` output
-  if (sum(!(display_columns %in% names(x))) >= 1) {
-    stop("as_gt: the variable names in display_columns is not outputted in the summary_bound object!")
-  } else {
-    x <- x %>% dplyr::select(dplyr::all_of(display_columns))
-  }
+  if (!all(columns %in% names(x))) stop(
+    "not all variable names in 'display_columns' are in the summary_bound object!"
+  )
+  columns
+}
 
-  # set different default footnotes to different methods
-  if (method == "ahr" && is.null(footnote)) {
-    footnote <- list(
-      content = c(
-        ifelse("~HR at bound" %in% display_columns,
-          "Approximate hazard ratio to cross bound.", NA
-        ),
-        ifelse("Nominal p" %in% display_columns,
-          "One-sided p-value for experimental vs control treatment.
-          Value < 0.5 favors experimental, > 0.5 favors control.", NA
-        )
-      ),
-      location = c(
-        ifelse("~HR at bound" %in% display_columns, "~HR at bound", NA),
-        ifelse("Nominal p" %in% display_columns, "Nominal p", NA)
-      ),
-      attr = c(
-        ifelse("~HR at bound" %in% display_columns, "colname", NA),
-        ifelse("Nominal p" %in% display_columns, "colname", NA)
-      )
-    )
-    footnote <- lapply(footnote, function(x) x[!is.na(x)])
-  }
-  if (method == "wlr" && is.null(footnote)) {
-    footnote <- list(
-      content = c(
-        ifelse("~wHR at bound" %in% display_columns,
-          "Approximate hazard ratio to cross bound.", NA
-        ),
-        ifelse("Nominal p" %in% display_columns,
-          "One-sided p-value for experimental vs control treatment.
-          Value < 0.5 favors experimental, > 0.5 favors control.", NA
-        ),
-        "wAHR is the weighted AHR."
-      ),
-      location = c(
-        ifelse("~wHR at bound" %in% display_columns, "~wHR at bound", NA),
-        ifelse("Nominal p" %in% display_columns, "Nominal p", NA),
-        NA
-      ),
-      attr = c(
-        ifelse("~wHR at bound" %in% display_columns, "colname", NA),
-        ifelse("Nominal p" %in% display_columns, "colname", NA),
-        "analysis"
-      )
-    )
-    footnote <- lapply(footnote, function(x) x[!is.na(x)])
-  }
-  if (method == "combo" && is.null(footnote)) {
-    footnote <- list(
-      content = c(
-        ifelse("Nominal p" %in% display_columns,
-          "One-sided p-value for experimental vs control treatment.
-               Value < 0.5 favors experimental, > 0.5 favors control.", NA
-        ),
-        "EF is event fraction. AHR  is under regular weighted log rank test."
-      ),
-      location = c(
-        ifelse("Nominal p" %in% display_columns, "Nominal p", NA),
-        NA
-      ),
-      attr = c(
-        ifelse("Nominal p" %in% display_columns, "colname", NA),
-        "analysis"
-      )
-    )
-    footnote <- lapply(footnote, function(x) x[!is.na(x)])
-  }
-  if (method == "rd" && is.null(footnote)) {
-    footnote <- list(
-      content = c(ifelse("Nominal p" %in% display_columns,
-        "One-sided p-value for experimental vs control treatment.
-                         Value < 0.5 favors experimental, > 0.5 favors control.", NA
-      )),
-      location = c(ifelse("Nominal p" %in% display_columns, "Nominal p", NA)),
-      attr = c(ifelse("Nominal p" %in% display_columns, "colname", NA))
-    )
-    footnote <- lapply(footnote, function(x) x[!is.na(x)])
+# default footnotes for 'gs_design' tables
+gsd_footnote <- function(method, columns) {
+  n <- c("Nominal p", "~HR at bound", "~wHR at bound")
+  i <- n %in% columns
+  res <- if (i[1]) list(
+    content = paste(
+      "One-sided p-value for experimental vs control treatment.",
+      "Value < 0.5 favors experimental, > 0.5 favors control."
+    ),
+    location = n[1], attr = "colname"
+  ) else {
+    list(content = NULL, location = NULL, attr = NULL)
   }
+  x <- "Approximate hazard ratio to cross bound."
+  switch(
+    method,
+    ahr = res %+% if (i[2]) list(x, n[2], "colname"),
+    wlr = res %+% (if (i[3]) list(x, n[3], "colname")) %+%
+      list("wAHR is the weighted AHR.", NULL, "analysis"),
+    combo = res %+% list(
+      "EF is event fraction. AHR is under regular weighted log rank test.",
+      NULL, "analysis"
+    ),
+    rd = res
+  )
+}
 
-  # Filter out inf bound ----
-  x <- x %>%
-    subset(!is.na(`Alternate hypothesis`)) %>%
-    subset(!is.na(`Null hypothesis`))
+# footnote for non-binding designs
+gsd_footnote_nb <- function(x, x_alpha, full_alpha) {
+  if (!inherits(x, "non_binding") || x_alpha >= full_alpha) return()
+  a1 <- format(x_alpha, scientific = FALSE)
+  a2 <- format(full_alpha, scientific = FALSE)
+  a3 <- format(full_alpha - x_alpha, scientific = FALSE)
+  paste0(
+    "Cumulative alpha for final analysis ",
+    "(", a1, ") ", "is less than the full alpha ", "(", a2, ") ",
+    "when the futility bound is non-binding. ",
+    "The smaller value subtracts the probability of crossing a futility bound ",
+    "before crossing an efficacy bound at a later analysis ",
+    "(", a2, " - ", a3, " = ", a1, ") ", "under the null hypothesis."
+  )
+}
 
-  # Add spanner ----
-  names(x)[names(x) == "Alternate hypothesis"] <- colname_spannersub[1]
-  names(x)[names(x) == "Null hypothesis"] <- colname_spannersub[2]
+# where to add the non-binding design footnote
+gsd_footnote_row <- function(x, bound) {
+  # for a vector of "Analysis: N", get a logical vector `i`, in which `TRUE`
+  # indicates the position of the largest `N`
+  a <- x$Analysis
+  r <- "^Analysis: ([0-9]+).*"
+  i <- grepl(r, a)
+  k <- as.numeric(sub(r, '\\1', a[i]))
+  i[i] <- k == max(k)
+  i & x$Bound == bound
+}
 
-  x <- x %>%
-    subset(Bound %in% display_bound) %>%
-    dplyr::arrange(Analysis) %>%
-    dplyr::group_by(Analysis) %>%
-    gt::gt() %>%
-    gt::tab_spanner(
-      columns = dplyr::all_of(colname_spannersub),
-      label = colname_spanner
-    ) %>%
-    gt::tab_header(title = title, subtitle = subtitle)
+# a list of information for `as_[gt|rtf].gs_design()` methods: the transformed
+# data, title, and footnote, etc.
+gsd_parts <- function(
+    x, title, subtitle, spannersub, footnote, bound, columns, inf_bound,
+    alpha_column = spannersub[2], transform = identity
+) {
+  method <- intersect(c("ahr", "wlr", "combo", "rd"), class(x))[1]
+  if (!inf_bound) x <- filter(x, !is.infinite(Z))
+  # `x` needs a custom transformation in as_rtf()
+  x2 <- transform(x)
 
-  # Add footnotes ----
-  if (!is.null(footnote$content)) {
-    if (length(footnote$content) != 0) {
-      for (i in seq_along(footnote$content)) {
-        # if the footnotes is added on the colnames
-        if (footnote$attr[i] == "colname") {
-          x <- x %>%
-            gt::tab_footnote(
-              footnote = footnote$content[i],
-              locations = gt::cells_column_labels(columns = footnote$location[i])
-            )
-        }
-        # if the footnotes is added on the title/subtitle
-        if (footnote$attr[i] == "title" || footnote$attr[i] == "subtitle") {
-          x <- x %>%
-            gt::tab_footnote(
-              footnote = footnote$content[i],
-              locations = gt::cells_title(group = footnote$attr[i])
-            )
-        }
-        # if the footnotes is added on the analysis summary row, which is a grouping variable, i.e., Analysis
-        if (footnote$attr[i] == "analysis") {
-          x <- x %>%
-            gt::tab_footnote(
-              footnote = footnote$content[i],
-              locations = gt::cells_row_groups(groups = dplyr::starts_with("Analysis"))
-            )
-        }
-        # if the footnotes is added on the column spanner
-        if (footnote$attr[i] == "spanner") {
-          x <- x %>%
-            gt::tab_footnote(
-              footnote = footnote$content[i],
-              locations = gt::cells_column_spanners(spanners = colname_spanner)
-            )
-        }
-      }
-    }
-  }
+  columns <- gsd_columns(columns, method, x2)
+  x2 <- x2[, columns]
+  x2 <- subset(x2, !is.na(`Alternate hypothesis`) & !is.na(`Null hypothesis`))
+  x2 <- subset(x2, Bound %in% bound)
 
-  ## if it is non-binding design
-  if (x_non_binding && (x_alpha < full_alpha)) {
-    x <- x %>%
-      gt::tab_footnote(
-        footnote = paste0(
-          "Cumulative alpha for final analysis ",
-          "(", format(x_alpha, scientific = FALSE), ") ",
-          "is less than the full alpha ",
-          "(", format(full_alpha, scientific = FALSE), ") ",
-          "when the futility bound is non-binding. ",
-          "The smaller value subtracts the probability of ",
-          "crossing a futility bound before ",
-          "crossing an efficacy bound at a later analysis ",
-          "(",
-          format(full_alpha, scientific = FALSE),
-          " - ",
-          format(full_alpha - x_alpha, scientific = FALSE),
-          " = ",
-          format(x_alpha, scientific = FALSE),
-          ") ",
-          "under the null hypothesis."
-        ),
-        locations = gt::cells_body(
-          columns = colname_spannersub[2],
-          rows = (substring(x_old$Analysis, 1, 11) == paste0("Analysis: ", max(x_k))) &
-            (x_old$Bound == display_bound[1])
-        )
-      )
-  }
+  i <- match(c("Alternate hypothesis", "Null hypothesis"), names(x2))
+  names(x2)[i] <- spannersub
 
-  return(x)
+  title <- title %||% paste("Bound summary", switch(
+    method,
+    ahr = "for AHR design", wlr = "for WLR design",
+    combo = "for MaxCombo design", rd = "of Binary Endpoint"
+  ))
+  subtitle <- subtitle %||% switch(
+    method,
+    ahr = "AHR approximations of ~HR at bound",
+    wlr = "WLR approximation of ~wHR at bound",
+    combo = "MaxCombo approximation",
+    rd = "measured by risk difference"
+  )
+
+  list(
+    x = dplyr::arrange(x2, Analysis),
+    title = title, subtitle = subtitle,
+    footnote = footnote %||% gsd_footnote(method, columns),
+    alpha = max(filter(x, Bound == bound[1])[[alpha_column]])
+  )
 }
diff --git a/R/as_rtf.R b/R/as_rtf.R
index 8e009d3e..e317aff4 100644
--- a/R/as_rtf.R
+++ b/R/as_rtf.R
@@ -101,140 +101,23 @@ as_rtf.fixed_design <- function(
     file,
     ...) {
   orientation <- match.arg(orientation)
-
-  # get the design method
-  if ("ahr" %in% class(x)) {
-    design_mtd <- "ahr"
-  } else if ("fh" %in% class(x)) {
-    design_mtd <- "fh"
-  } else if ("mb" %in% class(x)) {
-    design_mtd <- "mb"
-  } else if ("lf" %in% class(x)) {
-    design_mtd <- "lf"
-  } else if ("rd" %in% class(x)) {
-    design_mtd <- "rd"
-  } else if ("maxcombo" %in% class(x)) {
-    design_mtd <- "maxcombo"
-  } else if ("milestone" %in% class(x)) {
-    design_mtd <- "milestone"
-  } else if ("rmst" %in% class(x)) {
-    design_mtd <- "rmst"
-  } else if ("rd" %in% class(x)) {
-    design_mtd <- "rd"
-  }
-
-  # set the default title
-  if (is.null(title)) {
-    title <- switch(design_mtd,
-      "ahr" = {
-        paste0("Fixed Design under AHR Method", " {^a}")
-      },
-      "fh" = {
-        paste0("Fixed Design under Fleming-Harrington Method", " {^a}")
-      },
-      "mb" = {
-        paste0("Fixed Design under Magirr-Burman Method", " {^a}")
-      },
-      "lf" = {
-        paste0("Fixed Design under Lachin and Foulkes Method", " {^a}")
-      },
-      "rd" = {
-        paste0("Fixed Design of Risk Difference under Farrington-Manning Method", " {^a}")
-      },
-      "maxcombo" = {
-        paste0("Fixed Design under MaxCombo Method", " {^a}")
-      },
-      "milestone" = {
-        paste0("Fixed Design under Milestone Method", " {^a}")
-      },
-      "rmst" = {
-        paste0("Fixed Design under Restricted Mean Survival Time Method", " {^a}")
-      },
-      "rd" = {
-        paste0("Fixed Design of Risk Difference", " {^a}")
-      }
-    )
-  }
-
-
-  # set the default footnote
-  if (is.null(footnote)) {
-    footnote <- switch(design_mtd,
-      "ahr" = {
-        paste0("{^a} ", "Power computed with average hazard ratio method.")
-      },
-      "fh" = {
-        paste0(
-          "{^a} ",
-          "Power for Fleming-Harrington test ",
-          substr(x$Design, 19, nchar(x$Design)),
-          " using method of Yung and Liu."
-        )
-      },
-      "mb" = {
-        paste0(
-          "{^a} ",
-          "Power for ",
-          x$Design,
-          " computed with method of Yung and Liu."
-        )
-      },
-      "lf" = {
-        paste0(
-          "{^a} ",
-          "Power using Lachin and Foulkes method applied
-          using expected average hazard ratio (AHR) at time of planned analysis."
-        )
-      },
-      "rd" = {
-        paste0(
-          "{^a} ",
-          "Risk difference power without continuity correction using method of Farrington and Manning."
-        )
-      },
-      "maxcombo" = {
-        paste0(
-          "{^a} ",
-          "Power for MaxCombo test with Fleming-Harrington tests",
-          substr(x$Design, 9, nchar(x$Design)), "."
-        )
-      },
-      "milestone" = {
-        paste0("{^a} ", "Power for ", x$Design, " computed with method of Yung and Liu.")
-      },
-      "rmst" = {
-        paste0("{^a} ", "Power for ", x$Design, " computed with method of Yung and Liu.")
-      }
-    )
-  }
+  method <- fd_method(x)
+  title <- title %||% paste(fd_title(method), "{^a}")
+  footnote <- footnote %||% paste("{^a}", fd_footnote(x, method))
 
   # set default column width
   n_row <- nrow(x)
   n_col <- ncol(x)
-  if (!is.null(col_rel_width) && !(n_col == length(col_rel_width))) {
-    stop(
-      "col_rel_width must have the same length (has ",
-      length(col_rel_width),
-      ") as `x` has number of columns (has ",
-      n_col, ").",
-      call. = FALSE
-    )
-  }
+  check_rel_width(col_rel_width, n_col)
 
   # set column header
-  colheader <-
-    paste0(paste(names(x), collapse = " | "))
+  colheader <- paste(names(x), collapse = " | ")
 
   # set relative width
-  if (is.null(col_rel_width)) {
-    rel_width <- c(2, rep(1, (n_col - 1)))
-  } else {
-    rel_width <- col_rel_width
-  }
+  rel_width <- col_rel_width %||% c(2, rep(1, n_col - 1))
 
   # Column boarder
-  border_top <- rep("single", n_col)
-  border_left <- rep("single", n_col)
+  border_top <- border_left <- rep("single", n_col)
 
   # Using order number to customize row format
   text_justification <- c("l", rep("c", n_col - 1))
@@ -245,13 +128,9 @@ as_rtf.fixed_design <- function(
   ans <- x %>%
     r2rtf::rtf_page(orientation = orientation) %>%
     r2rtf::rtf_title(title) %>%
-    r2rtf::rtf_colheader(
-      colheader = colheader,
-      col_rel_width = rel_width,
-      text_font_size = text_font_size
-    ) %>%
+    r2rtf::rtf_colheader(colheader, rel_width, text_font_size = text_font_size) %>%
     r2rtf::rtf_body(
-      col_rel_width = rel_width,
+      rel_width,
       border_left = border_left,
       border_top = border_top,
       text_justification = text_justification,
@@ -261,21 +140,19 @@ as_rtf.fixed_design <- function(
       text_font_size = text_font_size
     )
 
-  if (!is.null(footnote)) {
-    ans <- ans %>%
-      r2rtf::rtf_footnote(footnote,
-        text_font_size = text_font_size
-      )
-  }
-
   # Prepare output
-  ans %>%
-    r2rtf::rtf_encode() %>%
-    r2rtf::write_rtf(file = file)
+  rtf_write(ans, file, footnote, text_font_size)
 
   invisible(x)
 }
 
+check_rel_width <- function(width, n_col) {
+  if (!is.null(width) && n_col != length(width)) stop(
+    "The length of 'col_rel_width' (", length(width), ") differs with ",
+    "the number of columns in 'x' (", n_col, ")."
+  )
+}
+
 #' @rdname  as_rtf
 #'
 #' @param title A string to specify the title of the RTF table.
@@ -413,242 +290,43 @@ as_rtf.gs_design <- function(
     file,
     ...) {
   orientation <- match.arg(orientation)
-
-  method <- class(x)[class(x) %in% c("ahr", "wlr", "combo", "rd")]
-  x_alpha <- max((x %>% dplyr::filter(Bound == display_bound[1]))[["Null hypothesis"]])
-  x_non_binding <- "non_binding" %in% class(x)
-  x_k <- lapply(x$Analysis, function(x) {
-    return(as.numeric(substring(x, 11, 11)))
-  }) %>% unlist()
   x_old <- x
 
-  x <- data.frame(lapply(x, function(x) trimws(formatC(x, flag = "-"), "r")))
-  names(x) <- names(x_old)
-
-  # Set defaults ----
-  # set different default title to different methods
-  if (method == "ahr" && is.null(title)) {
-    title <- "Bound summary for AHR design"
-  }
-  if (method == "wlr" && is.null(title)) {
-    title <- "Bound summary for WLR design"
-  }
-  if (method == "combo" && is.null(title)) {
-    title <- "Bound summary for MaxCombo design"
-  }
-
-  if (method == "rd" && is.null(title)) {
-    title <- "Bound summary of Binary Endpoint"
-  }
-
-  # set different default subtitle to different methods
-  if (method == "ahr" && is.null(subtitle)) {
-    subtitle <- "AHR approximations of ~HR at bound"
-  }
-  if (method == "wlr" && is.null(subtitle)) {
-    subtitle <- "WLR approximation of ~wHR at bound"
-  }
-  if (method == "combo" && is.null(subtitle)) {
-    subtitle <- "MaxCombo approximation"
-  }
-  if (method == "rd" && is.null(subtitle)) {
-    subtitle <- "measured by risk difference"
-  }
-
-  # set different default columns to display
-  if (is.null(display_columns)) {
-    if (method == "ahr") {
-      display_columns <- c(
-        "Analysis", "Bound", "Z", "Nominal p",
-        "~HR at bound", "Alternate hypothesis", "Null hypothesis"
-      )
-    } else if (method == "wlr") {
-      display_columns <- c(
-        "Analysis", "Bound", "Z", "Nominal p",
-        "~wHR at bound", "Alternate hypothesis", "Null hypothesis"
-      )
-    } else if (method == "combo") {
-      display_columns <- c(
-        "Analysis", "Bound", "Z", "Nominal p",
-        "Alternate hypothesis", "Null hypothesis"
-      )
-    } else if (method == "rd") {
-      display_columns <- c(
-        "Analysis", "Bound", "Z", "Nominal p",
-        "~Risk difference at bound", "Alternate hypothesis", "Null hypothesis"
-      )
+  parts <- gsd_parts(
+    x, title, subtitle, colname_spannersub, footnote,
+    display_bound, display_columns, display_inf_bound, "Null hypothesis",
+    function(x) {
+      x2 <- data.frame(lapply(x, function(x) trimws(formatC(x, flag = "-"), "r")))
+      names(x2) <- names(x)
+      x2
     }
-  }
-  # filter the columns to display as the output
-  ## if `Probability` is selected to output, then transform it to `c("Alternate hypothesis", "Null hypothesis")`
-  if ("Probability" %in% display_columns) {
-    display_columns <- display_columns[!display_columns == "Probability"]
-    display_columns <- c(display_columns, "Alternate hypothesis", "Null hypothesis")
-  }
-  ## check if the `display_columns` are included in `x` output
-  if (sum(!(display_columns %in% names(x))) >= 1) {
-    stop("as_rtf: the variable names in display_columns is not outputted in the summary_bound object!")
-  } else {
-    x <- x %>% dplyr::select(dplyr::all_of(display_columns))
-  }
-
-  # set different default footnotes to different methods
-  if (method == "ahr" && is.null(footnote)) {
-    footnote <- list(
-      content = c(
-        ifelse(
-          "Nominal p" %in% display_columns,
-          paste(
-            "One-sided p-value for experimental vs control treatment.",
-            "Value < 0.5 favors experimental, > 0.5 favors control."
-          ),
-          NA
-        ),
-        ifelse(
-          "~HR at bound" %in% display_columns,
-          "Approximate hazard ratio to cross bound.",
-          NA
-        )
-      ),
-      location = c(
-        ifelse("Nominal p" %in% display_columns, "Nominal p", NA),
-        ifelse("~HR at bound" %in% display_columns, "~HR at bound", NA)
-      ),
-      attr = c(
-        ifelse("Nominal p" %in% display_columns, "colname", NA),
-        ifelse("~HR at bound" %in% display_columns, "colname", NA)
-      )
-    )
-    footnote <- lapply(footnote, function(x) x[!is.na(x)])
-  }
-  if (method == "wlr" && is.null(footnote)) {
-    footnote <- list(
-      content = c(
-        ifelse(
-          "Nominal p" %in% display_columns,
-          paste(
-            "One-sided p-value for experimental vs control treatment.",
-            "Value < 0.5 favors experimental, > 0.5 favors control."
-          ),
-          NA
-        ),
-        ifelse(
-          "~wHR at bound" %in% display_columns,
-          "Approximate hazard ratio to cross bound.",
-          NA
-        ),
-        "wAHR is the weighted AHR."
-      ),
-      location = c(
-        ifelse("Nominal p" %in% display_columns, "Nominal p", NA),
-        ifelse("~wHR at bound" %in% display_columns, "~wHR at bound", NA),
-        NA
-      ),
-      attr = c(
-        ifelse("Nominal p" %in% display_columns, "colname", NA),
-        ifelse("~wHR at bound" %in% display_columns, "colname", NA),
-        "analysis"
-      )
-    )
-    footnote <- lapply(footnote, function(x) x[!is.na(x)])
-  }
-  if (method == "combo" && is.null(footnote)) {
-    footnote <- list(
-      content = c(
-        ifelse(
-          "Nominal p" %in% display_columns,
-          paste(
-            "One-sided p-value for experimental vs control treatment.",
-            "Value < 0.5 favors experimental, > 0.5 favors control."
-          ),
-          NA
-        ),
-        "EF is event fraction. AHR  is under regular weighted log rank test."
-      ),
-      location = c(
-        ifelse("Nominal p" %in% display_columns, "Nominal p", NA),
-        NA
-      ),
-      attr = c(
-        ifelse("Nominal p" %in% display_columns, "colname", NA),
-        "analysis"
-      )
-    )
-    footnote <- lapply(footnote, function(x) x[!is.na(x)])
-  }
-  if (method == "rd" && is.null(footnote)) {
-    footnote <- list(
-      content = c(ifelse(
-        "Nominal p" %in% display_columns,
-        paste(
-          "One-sided p-value for experimental vs control treatment.",
-          "Value < 0.5 favors experimental, > 0.5 favors control."
-        ),
-        NA
-      )),
-      location = c(ifelse("Nominal p" %in% display_columns, "Nominal p", NA)),
-      attr = c(ifelse("Nominal p" %in% display_columns, "colname", NA))
-    )
-    footnote <- lapply(footnote, function(x) x[!is.na(x)])
-  }
-
-  # Filter out inf bound ----
-  x <- x %>%
-    subset(!is.na(`Alternate hypothesis`)) %>%
-    subset(!is.na(`Null hypothesis`))
-
-  # organize data
-  x <- x %>%
-    subset(Bound %in% display_bound) %>%
-    dplyr::arrange(Analysis)
+  )
+  x <- parts$x
+  title <- parts$title
+  subtitle <- parts$subtitle
 
   # Set rtf parameters ----
   n_col <- ncol(x)
   n_row <- nrow(x)
-  if (!is.null(col_rel_width) && !(n_col == length(col_rel_width))) {
-    stop(
-      "col_rel_width must have the same length (has ",
-      length(col_rel_width),
-      ") as `x` has number of columns (has ",
-      n_col, ").",
-      call. = FALSE
-    )
-  }
-
-  # set column header
-  names(x)[names(x) == "Alternate hypothesis"] <- colname_spannersub[1]
-  names(x)[names(x) == "Null hypothesis"] <- colname_spannersub[2]
-
+  check_rel_width(col_rel_width, n_col)
   colheader <- c(
     paste0(" | ", colname_spanner),
     paste(names(x)[-1], collapse = " | ")
   )
 
   # set relative width
-  if (is.null(col_rel_width)) {
-    rel_width_body <- rep(1, n_col)
-  } else {
-    rel_width_body <- col_rel_width
-  }
+  rel_width_body <- col_rel_width %||% rep(1, n_col)
 
-  rel_width_head <- rel_width_body[2:length(rel_width_body)]
+  rel_width_head <- rel_width_body[-1]
   rel_width_head <- list(
-    c(
-      sum(rel_width_head[2:(n_col - 2)]),
-      sum(tail(rel_width_head, n = 2))
-    ),
+    c(sum(rel_width_head[2:(n_col - 2)]), sum(tail(rel_width_head, 2))),
     rel_width_head
   )
 
   # column boarder
-  border_top_head <- rep("single", (n_col - 1))
-  border_top_body <- rep("single", n_col)
-  border_bottom <- rep("single", n_col)
-  border_left_head <- list(
-    c("single", "single"),
-    rep("single", n_col - 1)
-  )
-  border_left_body <- c("single", border_left_head[[2]])
+  border_top_body <- border_bottom <- border_left_body <- rep("single", n_col)
+  border_top_head <- border_top_body[-1]
+  border_left_head <- list(rep("single", 2), border_top_head)
 
   # Using order number to customize row format
   text_justification <- c("l", "l", rep("c", n_col - 2))
@@ -658,108 +336,62 @@ as_rtf.gs_design <- function(
   # Add footnotes ----
   # initialization for footnote
   footnotes <- NULL
-  alpha_utf_int <- 96
-
-  if (!is.null(footnote$content)) {
-    if (length(footnote$content) > 0) {
-      for (i in seq_along(footnote$content)) {
-        alpha_utf_int <- alpha_utf_int + 1
-        if (footnote$attr[i] == "colname") {
-          colheader[2] <- sub(
-            footnote$location[i],
-            paste0(footnote$location[i], " {^", intToUtf8(alpha_utf_int), "}"),
-            colheader[2]
-          )
-        } else if (footnote$attr[i] == "title") {
-          title <- paste0(title, " \\super ", intToUtf8(alpha_utf_int))
-        } else if (footnote$attr[i] == "subtitle") {
-          subtitle <- paste0(subtitle, " {\\super ", intToUtf8(alpha_utf_int), "}")
-        } else if (footnote$attr[i] == "analysis") {
-          x["Analysis"] <- lapply(x["Analysis"], function(z) paste0(z, " {^", intToUtf8(alpha_utf_int), "}"))
-        } else if (footnote$attr[i] == "spanner") {
-          colheader[1] <- sub(
-            colname_spanner,
-            paste0(colname_spanner, " {^", intToUtf8(alpha_utf_int), "}"),
-            colheader[1]
-          )
-        }
-        marked_footnote <- paste0("{\\super ", intToUtf8(alpha_utf_int), "} ", footnote$content[i])
-        if (!is.null(footnotes)) {
-          footnotes <- paste0(footnotes, "\\line", marked_footnote)
-        } else {
-          footnotes <- marked_footnote
-        }
-      }
+  footnote <- parts$footnote
+  # footnote markers (a, b, c, ... from letters[idx])
+  idx <- 0L
+  marker <- function() letters[idx <<- idx + 1L]
+
+  for (i in seq_along(footnote$content)) {
+    att <- footnote$attr[i]
+    mkr <- marker()
+    if (att == "colname") {
+      colheader[2] <- sub(
+        footnote$location[i],
+        paste0(footnote$location[i], " {^", mkr, "}"),
+        colheader[2]
+      )
+    } else if (att == "title") {
+      title <- paste0(title, " \\super ", mkr)
+    } else if (att == "subtitle") {
+      subtitle <- paste0(subtitle, " {\\super ", mkr, "}")
+    } else if (att == "analysis") {
+      x["Analysis"] <- lapply(x["Analysis"], function(z) paste0(z, " {^", mkr, "}"))
+    } else if (att == "spanner") {
+      colheader[1] <- sub(
+        colname_spanner,
+        paste0(colname_spanner, " {^", mkr, "}"),
+        colheader[1]
+      )
     }
+    marked_footnote <- paste0("{\\super ", mkr, "} ", footnote$content[i])
+    footnotes <- c(footnotes, marked_footnote)
   }
 
-  ## if it is non-binding design
-  if (x_non_binding && (x_alpha < full_alpha)) {
-    alpha_utf_int <- alpha_utf_int + 1
-
-    x[
-      (substring(x$Analysis, 1, 11) == paste0("Analysis: ", max(x_k))) &
-        x$Bound == display_bound[1], colname_spannersub[2]
-    ] <- paste0(
-      x[
-        (substring(x$Analysis, 1, 11) == paste0("Analysis: ", max(x_k))) &
-          x$Bound == display_bound[1], colname_spannersub[2]
-      ],
-      " {^", intToUtf8(alpha_utf_int), "}"
-    )
-
-    footnote_non_binding <- paste0(
-      "{\\super ", intToUtf8(alpha_utf_int), "} ",
-      "Cumulative alpha for final analysis ",
-      "(", format(x_alpha, scientific = FALSE), ") ",
-      "is less than the full alpha ",
-      "(", format(full_alpha, scientific = FALSE), ") ",
-      "when the futility bound is non-binding. ",
-      "The smaller value subtracts the probability of ",
-      "crossing a futility bound before ",
-      "crossing an efficacy bound at a later analysis ",
-      "(",
-      format(full_alpha, scientific = FALSE),
-      " - ",
-      format(full_alpha - x_alpha, scientific = FALSE),
-      " = ",
-      format(x_alpha, scientific = FALSE),
-      ") ",
-      "under the null hypothesis."
-    )
-
-    if (!is.null(footnotes)) {
-      footnotes <- paste0(footnotes, "\\line", footnote_non_binding)
-    } else {
-      footnotes <- footnote_non_binding
-    }
+  # add footnote for non-binding design
+  footnote_nb <- gsd_footnote_nb(x_old, parts$alpha, full_alpha)
+  if (!is.null(footnote_nb)) {
+    mkr <- marker()
+    i <- gsd_footnote_row(x, display_bound[1])
+    j <- colname_spannersub[2]
+    x[i, j] <- paste0(x[i, j], " {^", mkr, "}")
+    footnotes <- c(footnotes, paste0("{\\super ", mkr, "} ", footnote_nb))
   }
 
   # Output ----
   # use r2rtf
   ans <- x %>%
     r2rtf::rtf_page(orientation = orientation) %>%
-    r2rtf::rtf_title(
-      title = title,
-      subtitle = subtitle,
-      text_convert = FALSE
-    ) %>%
+    r2rtf::rtf_title(title, subtitle, text_convert = FALSE) %>%
     r2rtf::rtf_colheader(
-      colheader = colheader[1],
-      col_rel_width = rel_width_head[[1]],
-      text_font_size = text_font_size,
-      border_left = border_left_head[[1]]
+      colheader[1], rel_width_head[[1]], border_left_head[[1]],
+      text_font_size = text_font_size
     ) %>%
     r2rtf::rtf_colheader(
-      colheader = colheader[2],
-      border_top = border_top_head,
-      border_left = border_left_head[[2]],
-      col_rel_width = rel_width_head[[2]],
-      text_font_size = text_font_size
+      colheader[2], rel_width_head[[2]], border_left_head[[2]],
+      border_top = border_top_head, text_font_size = text_font_size
     ) %>%
     r2rtf::rtf_body(
-      page_by = "Analysis",
-      col_rel_width = rel_width_body,
+      rel_width_body, page_by = "Analysis",
       border_left = border_left_body,
       border_top = border_top_body,
       border_bottom = border_bottom,
@@ -770,18 +402,17 @@ as_rtf.gs_design <- function(
       text_font_size = text_font_size
     )
 
-  if (!is.null(footnotes)) {
-    ans <- ans %>%
-      r2rtf::rtf_footnote(footnotes,
-        text_font_size = text_font_size,
-        text_convert = FALSE
-      )
-  }
-
   # Prepare output
-  ans %>%
-    r2rtf::rtf_encode() %>%
-    r2rtf::write_rtf(file = file)
+  rtf_write(ans, file, footnotes, text_font_size, text_convert = FALSE)
 
   invisible(x_old)
 }
+
+# write RTF with (optional) footnotes
+rtf_write <- function(x, file, footnote = NULL, size, ...) {
+  if (!is.null(footnote)) {
+    footnote <- paste(footnote, collapse = "\\line")
+    x <- r2rtf::rtf_footnote(x, footnote, text_font_size = size, ...)
+  }
+  r2rtf::write_rtf(r2rtf::rtf_encode(x), file)
+}
diff --git a/R/fixed_design_mb.R b/R/fixed_design_mb.R
index db90d001..9c27bf0f 100644
--- a/R/fixed_design_mb.R
+++ b/R/fixed_design_mb.R
@@ -23,7 +23,7 @@
 #' @param ratio Experimental:Control randomization ratio.
 #' @param study_duration Study duration.
 #' @param tau Test parameter of Magirr-Burman method.
-#'
+#' @param w_max Test parameter of Magirr-Burman method.
 #' @export
 #'
 #' @rdname fixed_design
@@ -43,7 +43,8 @@
 #'     dropout_rate = .001
 #'   ),
 #'   study_duration = 36,
-#'   tau = 4
+#'   tau = 4,
+#'   w_max = 2
 #' )
 #' x %>% summary()
 #'
@@ -58,7 +59,8 @@
 #'     dropout_rate = .001
 #'   ),
 #'   study_duration = 36,
-#'   tau = 4
+#'   tau = 4,
+#'   w_max = 2
 #' )
 #' x %>% summary()
 #'
@@ -69,7 +71,8 @@ fixed_design_mb <- function(
     study_duration = 36,
     enroll_rate,
     fail_rate,
-    tau = 6) {
+    tau = 6,
+    w_max = Inf) {
   # Check inputs ----
   check_enroll_rate(enroll_rate)
   check_fail_rate(fail_rate)
@@ -88,7 +91,7 @@ fixed_design_mb <- function(
 
   # Generate design ----
   weight <- function(x, arm0, arm1) {
-    wlr_weight_fh(x, arm0, arm1, rho = -1, gamma = 0, tau = tau)
+    wlr_weight_mb(x, arm0, arm1, tau = tau, w_max = w_max)
   }
   if (is.null(power)) {
     d <- gs_power_wlr(
diff --git a/R/gs_spending_combo.R b/R/gs_spending_combo.R
index 34518f50..617b9c30 100644
--- a/R/gs_spending_combo.R
+++ b/R/gs_spending_combo.R
@@ -78,13 +78,16 @@
 #' gs_spending_combo(par, info = 1:3 / 3)
 #'
 #' # Truncated, trimmed and gapped spending functions
-#' par <- list(sf = gsDesign::sfTruncated, total_spend = 0.025, param = list(trange = c(.2, .8), sf = gsDesign::sfHSD, param = 1))
+#' par <- list(sf = gsDesign::sfTruncated, total_spend = 0.025,
+#'   param = list(trange = c(.2, .8), sf = gsDesign::sfHSD, param = 1))
 #' gs_spending_combo(par, info = 1:3 / 3)
 #'
-#' par <- list(sf = gsDesign::sfTrimmed, total_spend = 0.025, param = list(trange = c(.2, .8), sf = gsDesign::sfHSD, param = 1))
+#' par <- list(sf = gsDesign::sfTrimmed, total_spend = 0.025,
+#'   param = list(trange = c(.2, .8), sf = gsDesign::sfHSD, param = 1))
 #' gs_spending_combo(par, info = 1:3 / 3)
 #'
-#' par <- list(sf = gsDesign::sfGapped, total_spend = 0.025, param = list(trange = c(.2, .8), sf = gsDesign::sfHSD, param = 1))
+#' par <- list(sf = gsDesign::sfGapped, total_spend = 0.025,
+#'   param = list(trange = c(.2, .8), sf = gsDesign::sfHSD, param = 1))
 #' gs_spending_combo(par, info = 1:3 / 3)
 #'
 #' # Xi and Gallo conditional error spending functions
diff --git a/R/pw_info.R b/R/pw_info.R
index 90f55339..0c5dd6b9 100644
--- a/R/pw_info.R
+++ b/R/pw_info.R
@@ -239,7 +239,7 @@ pw_info <- function(
   ans <- ans[order(t), .SD, by = .(time, stratum)]
 
   # filter out the rows with 0 events
-  ans <- ans[!is_almost_k(event, 0L)]
+  ans <- ans[!almost_equal(event, 0L)]
   setcolorder(ans, neworder = c("time", "stratum", "t", "hr", "n", "event", "info", "info0"))
 
   setDF(ans)
diff --git a/R/to_integer.R b/R/to_integer.R
index 9c16ac7f..f358c6be 100644
--- a/R/to_integer.R
+++ b/R/to_integer.R
@@ -98,7 +98,7 @@ to_integer.fixed_design <- function(x, sample_size = TRUE, ...) {
     mutate(rate = rate * ceiling(output_n / multiply_factor) * multiply_factor / output_n)
 
   # Round up the FA events
-  event_ceiling <- ceiling(x$analysis$event) |> as.integer()
+  event_ceiling <- ceiling(x$analysis$event)
 
   if ((x$design == "ahr") && (input_n != output_n)) {
     x_new <- gs_power_ahr(
@@ -200,13 +200,8 @@ to_integer.fixed_design <- function(x, sample_size = TRUE, ...) {
 
   # Make n and event of ans$analysis exactly integers
   if ("fixed_design" %in% class(ans)) {
-    if (is_almost_k(x = ans$analysis$n, k = round(ans$analysis$n))) {
-      ans$analysis$n <- round(ans$analysis$n)
-    }
-
-    if (is_almost_k(x = ans$analysis$event, k = round(ans$analysis$event))) {
-      ans$analysis$event <- round(ans$analysis$event)
-    }
+    ans$analysis$n <- round(ans$analysis$n)
+    ans$analysis$event <- round(ans$analysis$event)
   }
 
   return(ans)
@@ -270,77 +265,24 @@ to_integer.fixed_design <- function(x, sample_size = TRUE, ...) {
 #' gsDesign::sfLDOF(alpha = 0.025, t = 18 / 30)$spend
 #' }
 to_integer.gs_design <- function(x, sample_size = TRUE, ...) {
+  is_ahr <- inherits(x, "ahr")
+  is_wlr <- inherits(x, "wlr")
+  is_rd  <- inherits(x, "rd")
+  if (!(is_ahr || is_wlr || is_rd)) {
+    message("The input object is not applicable to get an integer sample size.")
+    return(x)
+  }
+
   n_analysis <- length(x$analysis$analysis)
   multiply_factor <- x$input$ratio + 1
 
-  if ("ahr" %in% class(x)) {
-    # Updated events
-    event <- x$analysis$event
-    if (n_analysis == 1) {
-      event_new <- ceiling(event) %>% as.integer()
-    } else {
-      event_new <- c(floor(event[1:(n_analysis - 1)]), ceiling(event[n_analysis])) %>% as.integer()
-    }
-
-    # Updated sample size and enroll rate
-    sample_size_new <- (ceiling(x$analysis$n[n_analysis] / multiply_factor) * multiply_factor) %>% as.integer()
-    enroll_rate <- x$enroll_rate
-    enroll_rate_new <- enroll_rate %>%
-      mutate(rate = rate * sample_size_new / x$analysis$n[n_analysis])
-
-    # Updated upar
-    # If it is spending bounds
-    # Scenario 1: information-based spending
-    # Scenario 2: calendar-based spending
-    if (identical(x$input$upper, gs_b)) {
-      upar_new <- x$input$upar
-    } else if (identical(x$input$upper, gs_spending_bound)) {
-      upar_new <- x$input$upar
-      if (!("timing" %in% names(x$input$upar))) {
-        info_with_new_event <- gs_info_ahr(
-          enroll_rate = enroll_rate_new,
-          fail_rate = x$input$fail_rate,
-          ratio = x$input$ratio,
-          event = event_new,
-          analysis_time = NULL
-        )
-
-        upar_new$timing <- info_with_new_event$info / max(info_with_new_event$info)
-      }
-    }
-
-    # Updated lpar
-    if (identical(x$input$lower, gs_b)) {
-      lpar_new <- x$input$lpar
-    } else if (identical(x$input$lower, gs_spending_bound)) {
-      lpar_new <- x$input$lpar
-      if (!("timing" %in% names(x$input$lpar))) {
-        lpar_new$timing <- upar_new$timing
-      }
-    }
-
-    # Updated design with integer events and sample size
-    x_new <- gs_power_ahr(
-      enroll_rate = enroll_rate_new,
-      fail_rate = x$input$fail_rate,
-      event = event_new,
-      analysis_time = NULL,
-      ratio = x$input$ratio,
-      upper = x$input$upper, upar = upar_new,
-      lower = x$input$lower, lpar = lpar_new,
-      test_upper = x$input$test_upper,
-      test_lower = x$input$test_lower,
-      binding = x$input$binding,
-      info_scale = x$input$info_scale, r = x$input$r, tol = x$input$tol,
-      interval = c(0.01, max(x$analysis$time) + 100)
-    )
-  } else if ("wlr" %in% class(x)) {
+  if (!is_rd) {
     # Updated events to integer
     event <- x$analysis$event
     if (n_analysis == 1) {
-      event_new <- ceiling(event) %>% as.integer()
+      event_new <- ceiling(event)
     } else {
-      event_new <- c(floor(event[1:(n_analysis - 1)]), ceiling(event[n_analysis])) %>% as.integer()
+      event_new <- c(floor(event[1:(n_analysis - 1)]), ceiling(event[n_analysis]))
     }
 
     # Updated sample size to integer and enroll rates
@@ -384,7 +326,7 @@ to_integer.gs_design <- function(x, sample_size = TRUE, ...) {
     }
 
     # Updated design with integer events and sample size
-    x_new <- gs_power_wlr(
+    power_args <- list(
       enroll_rate = enroll_rate_new,
       fail_rate = x$input$fail_rate,
       event = event_new,
@@ -396,11 +338,11 @@ to_integer.gs_design <- function(x, sample_size = TRUE, ...) {
       test_lower = x$input$test_lower,
       binding = x$input$binding,
       info_scale = x$input$info_scale, r = x$input$r, tol = x$input$tol,
-      weight = x$input$weight,
-      approx = x$input$approx,
       interval = c(0.01, max(x$analysis$time) + 100)
     )
-  } else if ("rd" %in% class(x)) {
+    if (is_wlr) power_args[c("weight", "approx")] <- x$input[c("weight", "approx")]
+    x_new <- do.call(if (is_wlr) gs_power_wlr else gs_power_ahr, power_args)
+  } else {
     n_stratum <- length(x$input$p_c$stratum)
 
     # Update unstratified sample size to integer
@@ -413,27 +355,23 @@ to_integer.gs_design <- function(x, sample_size = TRUE, ...) {
     )
 
     # Update sample size per stratum
-    if (n_stratum == 1) {
-      suppressMessages(
-        tbl_n <- tibble::tibble(
-          analysis = rep(1:n_analysis, each = n_stratum),
-          stratum = rep(x$input$p_c$stratum, n_analysis)
-        ) %>%
-          left_join(sample_size_new)
+    suppressMessages({
+      tbl_n <- tibble::tibble(
+        analysis = rep(1:n_analysis, each = n_stratum),
+        stratum = rep(x$input$p_c$stratum, n_analysis)
       )
-    } else {
-      suppressMessages(
-        tbl_n <- tibble::tibble(
-          analysis = rep(1:n_analysis, each = n_stratum),
-          stratum = rep(x$input$p_c$stratum, n_analysis)
-        ) %>%
+      tbl_n <- if (n_stratum == 1) {
+        tbl_n %>%
+          left_join(sample_size_new)
+      } else {
+        tbl_n %>%
           left_join(x$input$stratum_prev) %>%
           left_join(sample_size_new) %>%
           mutate(n_new = prevalence * n) %>%
           select(-c(n, prevalence)) %>%
           dplyr::rename(n = n_new)
-      )
-    }
+      }
+    })
 
     # If it is spending bounds
     # Scenario 1: information-based spending
@@ -485,29 +423,11 @@ to_integer.gs_design <- function(x, sample_size = TRUE, ...) {
       r = x$input$r,
       tol = x$input$tol
     )
-  } else {
-    message("The input object is not applicable to get an integer sample size.")
-    x_new <- x
   }
 
   # Make n and event of x_new$analysis exactly integers
-  if ("ahr" %in% class(x) || "wlr" %in% class(x)) {
-    for (i in seq_along(n_analysis)) {
-      if (is_almost_k(x = x_new$analysis$n[i], k = round(x_new$analysis$n[i]))) {
-        x_new$analysis$n[i] <- round(x_new$analysis$n[i])
-      }
-
-      if (is_almost_k(x = x_new$analysis$event[i], k = round(x_new$analysis$event[i]))) {
-        x_new$analysis$event[i] <- round(x_new$analysis$event[i])
-      }
-    }
-  } else if ("rd" %in% class(x)) {
-    for (i in seq_along(n_analysis)) {
-      if (is_almost_k(x = x_new$analysis$n[i], k = round(x_new$analysis$n[i]))) {
-        x_new$analysis$n[i] <- round(x_new$analysis$n[i])
-      }
-    }
-  }
+  x_new$analysis$n <- round(x_new$analysis$n)
+  if (!is_rd) x_new$analysis$event <- round(x_new$analysis$event)
 
   return(x_new)
 }
diff --git a/R/utility_wlr.R b/R/utility_wlr.R
index 56c7c0f8..5622f29e 100644
--- a/R/utility_wlr.R
+++ b/R/utility_wlr.R
@@ -273,6 +273,6 @@ gs_sigma2_wlr <- function(arm0,
 }
 
 #' @noRd
-is_almost_k <- function(x, k, tol = .Machine$double.eps^0.5) {
+almost_equal <- function(x, k, tol = .Machine$double.eps^0.5) {
   abs(x - k) < tol
-}
\ No newline at end of file
+}
diff --git a/R/utils.R b/R/utils.R
new file mode 100644
index 00000000..bca42fde
--- /dev/null
+++ b/R/utils.R
@@ -0,0 +1,12 @@
+# %||% was introduced in base R 4.4.0
+if (!exists('%||%', baseenv(), inherits = FALSE)) `%||%` <- function(x, y) {
+  if (is.null(x)) y else x
+}
+
+# append elements from y to x
+`%+%` <- function(x, y) {
+  # append by names if available, otherwise append by integer indices
+  idx <- names(y) %||% seq_along(y)
+  for (i in idx) x[[i]] <- c(x[[i]], y[[i]])
+  x
+}
diff --git a/R/wlr_weight.R b/R/wlr_weight.R
index 14592cb5..4cc8f7fd 100644
--- a/R/wlr_weight.R
+++ b/R/wlr_weight.R
@@ -29,7 +29,7 @@
 #' @param rho A scalar parameter that controls the type of test.
 #' @param gamma A scalar parameter that controls the type of test.
 #' @param tau A scalar parameter of the cut-off time for modest weighted log rank test.
-#' @param wmax A scalar parameter of the cut-off weight for modest weighted log rank test.
+#' @param w_max A scalar parameter of the cut-off weight for modest weighted log rank test.
 #' @param power A scalar parameter that controls the power of the weight function.
 #'
 #' @section Specification:
@@ -171,7 +171,7 @@ wlr_weight_n <- function(x, arm0, arm1, power = 1) {
 #' arm0 <- gs_arm$arm0
 #' arm1 <- gs_arm$arm1
 #'
-#' wlr_weight_mb(1:3, arm0, arm1, tau = -1, wmax = 1.2)
-wlr_weight_mb <- function(x, arm0, arm1, tau = NULL, wmax = Inf) {
-  pmin(wmax, wlr_weight_fh(x, arm0, arm1, rho = -1, gamma = 0, tau = tau))
+#' wlr_weight_mb(1:3, arm0, arm1, tau = -1, w_max = 1.2)
+wlr_weight_mb <- function(x, arm0, arm1, tau = NULL, w_max = Inf) {
+  pmin(w_max, wlr_weight_fh(x, arm0, arm1, rho = -1, gamma = 0, tau = tau))
 }
diff --git a/man/fixed_design.Rd b/man/fixed_design.Rd
index cd61ddba..113dd28c 100644
--- a/man/fixed_design.Rd
+++ b/man/fixed_design.Rd
@@ -62,7 +62,8 @@ fixed_design_mb(
   study_duration = 36,
   enroll_rate,
   fail_rate,
-  tau = 6
+  tau = 6,
+  w_max = Inf
 )
 
 fixed_design_milestone(
@@ -117,6 +118,8 @@ and \code{1 - alpha} otherwise).}
 
 \item{tau}{Test parameter in RMST.}
 
+\item{w_max}{Test parameter of Magirr-Burman method.}
+
 \item{p_c}{A numerical value of the control arm rate.}
 
 \item{p_e}{A numerical value of the experimental arm rate.}
@@ -289,7 +292,8 @@ x <- fixed_design_mb(
     dropout_rate = .001
   ),
   study_duration = 36,
-  tau = 4
+  tau = 4,
+  w_max = 2
 )
 x \%>\% summary()
 
@@ -304,7 +308,8 @@ x <- fixed_design_mb(
     dropout_rate = .001
   ),
   study_duration = 36,
-  tau = 4
+  tau = 4,
+  w_max = 2
 )
 x \%>\% summary()
 
diff --git a/man/gs_spending_combo.Rd b/man/gs_spending_combo.Rd
index 38287a0c..b1c8cedc 100644
--- a/man/gs_spending_combo.Rd
+++ b/man/gs_spending_combo.Rd
@@ -80,13 +80,16 @@ par <- list(sf = gsDesign::sfPoints, total_spend = 0.025, param = c(.25, .25))
 gs_spending_combo(par, info = 1:3 / 3)
 
 # Truncated, trimmed and gapped spending functions
-par <- list(sf = gsDesign::sfTruncated, total_spend = 0.025, param = list(trange = c(.2, .8), sf = gsDesign::sfHSD, param = 1))
+par <- list(sf = gsDesign::sfTruncated, total_spend = 0.025,
+  param = list(trange = c(.2, .8), sf = gsDesign::sfHSD, param = 1))
 gs_spending_combo(par, info = 1:3 / 3)
 
-par <- list(sf = gsDesign::sfTrimmed, total_spend = 0.025, param = list(trange = c(.2, .8), sf = gsDesign::sfHSD, param = 1))
+par <- list(sf = gsDesign::sfTrimmed, total_spend = 0.025,
+  param = list(trange = c(.2, .8), sf = gsDesign::sfHSD, param = 1))
 gs_spending_combo(par, info = 1:3 / 3)
 
-par <- list(sf = gsDesign::sfGapped, total_spend = 0.025, param = list(trange = c(.2, .8), sf = gsDesign::sfHSD, param = 1))
+par <- list(sf = gsDesign::sfGapped, total_spend = 0.025,
+  param = list(trange = c(.2, .8), sf = gsDesign::sfHSD, param = 1))
 gs_spending_combo(par, info = 1:3 / 3)
 
 # Xi and Gallo conditional error spending functions
diff --git a/man/wlr_weight.Rd b/man/wlr_weight.Rd
index e1bcc5ca..c4a8bd0e 100644
--- a/man/wlr_weight.Rd
+++ b/man/wlr_weight.Rd
@@ -14,7 +14,7 @@ wlr_weight_1(x, arm0, arm1)
 
 wlr_weight_n(x, arm0, arm1, power = 1)
 
-wlr_weight_mb(x, arm0, arm1, tau = NULL, wmax = Inf)
+wlr_weight_mb(x, arm0, arm1, tau = NULL, w_max = Inf)
 }
 \arguments{
 \item{x}{A vector of numeric values.}
@@ -31,7 +31,7 @@ wlr_weight_mb(x, arm0, arm1, tau = NULL, wmax = Inf)
 
 \item{power}{A scalar parameter that controls the power of the weight function.}
 
-\item{wmax}{A scalar parameter of the cut-off weight for modest weighted log rank test.}
+\item{w_max}{A scalar parameter of the cut-off weight for modest weighted log rank test.}
 }
 \value{
 A vector of weights.
@@ -132,5 +132,5 @@ gs_arm <- gs_create_arm(enroll_rate, fail_rate, ratio = 1)
 arm0 <- gs_arm$arm0
 arm1 <- gs_arm$arm1
 
-wlr_weight_mb(1:3, arm0, arm1, tau = -1, wmax = 1.2)
+wlr_weight_mb(1:3, arm0, arm1, tau = -1, w_max = 1.2)
 }
diff --git a/tests/testthat/_snaps/independent_as_gt.md b/tests/testthat/_snaps/independent_as_gt.md
index 4568c13e..1ee9b113 100644
--- a/tests/testthat/_snaps/independent_as_gt.md
+++ b/tests/testthat/_snaps/independent_as_gt.md
@@ -79,8 +79,7 @@
     \bottomrule
     \end{longtable}
     \begin{minipage}{\linewidth}
-    \textsuperscript{\textit{1}}One-sided p-value for experimental vs control treatment.
-              Value < 0.5 favors experimental, > 0.5 favors control.\\
+    \textsuperscript{\textit{1}}One-sided p-value for experimental vs control treatment. Value < 0.5 favors experimental, > 0.5 favors control.\\
     \textsuperscript{\textit{2}}Approximate hazard ratio to cross bound.\\
     \end{minipage}
     \endgroup
@@ -117,8 +116,7 @@
     \bottomrule
     \end{longtable}
     \begin{minipage}{\linewidth}
-    \textsuperscript{\textit{1}}One-sided p-value for experimental vs control treatment.
-              Value < 0.5 favors experimental, > 0.5 favors control.\\
+    \textsuperscript{\textit{1}}One-sided p-value for experimental vs control treatment. Value < 0.5 favors experimental, > 0.5 favors control.\\
     \textsuperscript{\textit{2}}Approximate hazard ratio to cross bound.\\
     \end{minipage}
     \endgroup
@@ -144,8 +142,7 @@
     \bottomrule
     \end{longtable}
     \begin{minipage}{\linewidth}
-    \textsuperscript{\textit{1}}One-sided p-value for experimental vs control treatment.
-              Value < 0.5 favors experimental, > 0.5 favors control.\\
+    \textsuperscript{\textit{1}}One-sided p-value for experimental vs control treatment. Value < 0.5 favors experimental, > 0.5 favors control.\\
     \textsuperscript{\textit{2}}Approximate hazard ratio to cross bound.\\
     \textsuperscript{\textit{3}}wAHR is the weighted AHR.\\
     \end{minipage}
@@ -222,9 +219,8 @@
     \bottomrule
     \end{longtable}
     \begin{minipage}{\linewidth}
-    \textsuperscript{\textit{1}}One-sided p-value for experimental vs control treatment.
-                   Value < 0.5 favors experimental, > 0.5 favors control.\\
-    \textsuperscript{\textit{2}}EF is event fraction. AHR  is under regular weighted log rank test.\\
+    \textsuperscript{\textit{1}}One-sided p-value for experimental vs control treatment. Value < 0.5 favors experimental, > 0.5 favors control.\\
+    \textsuperscript{\textit{2}}EF is event fraction. AHR is under regular weighted log rank test.\\
     \end{minipage}
     \endgroup
 
@@ -249,8 +245,7 @@
     \bottomrule
     \end{longtable}
     \begin{minipage}{\linewidth}
-    \textsuperscript{\textit{1}}One-sided p-value for experimental vs control treatment.
-                             Value < 0.5 favors experimental, > 0.5 favors control.\\
+    \textsuperscript{\textit{1}}One-sided p-value for experimental vs control treatment. Value < 0.5 favors experimental, > 0.5 favors control.\\
     \end{minipage}
     \endgroup
 
@@ -284,8 +279,7 @@
     \bottomrule
     \end{longtable}
     \begin{minipage}{\linewidth}
-    \textsuperscript{\textit{1}}One-sided p-value for experimental vs control treatment.
-                             Value < 0.5 favors experimental, > 0.5 favors control.\\
+    \textsuperscript{\textit{1}}One-sided p-value for experimental vs control treatment. Value < 0.5 favors experimental, > 0.5 favors control.\\
     \textsuperscript{\textit{2}}Cumulative alpha for final analysis (0.0238) is less than the full alpha (0.025) when the futility bound is non-binding. The smaller value subtracts the probability of crossing a futility bound before crossing an efficacy bound at a later analysis (0.025 - 0.0012 = 0.0238) under the null hypothesis.\\
     \end{minipage}
     \endgroup
@@ -322,8 +316,7 @@
     \bottomrule
     \end{longtable}
     \begin{minipage}{\linewidth}
-    \textsuperscript{\textit{1}}One-sided p-value for experimental vs control treatment.
-              Value < 0.5 favors experimental, > 0.5 favors control.\\
+    \textsuperscript{\textit{1}}One-sided p-value for experimental vs control treatment. Value < 0.5 favors experimental, > 0.5 favors control.\\
     \textsuperscript{\textit{2}}Approximate hazard ratio to cross bound.\\
     \textsuperscript{\textit{3}}wAHR is the weighted AHR.\\
     \end{minipage}
@@ -361,8 +354,7 @@
     \bottomrule
     \end{longtable}
     \begin{minipage}{\linewidth}
-    \textsuperscript{\textit{1}}One-sided p-value for experimental vs control treatment.
-              Value < 0.5 favors experimental, > 0.5 favors control.\\
+    \textsuperscript{\textit{1}}One-sided p-value for experimental vs control treatment. Value < 0.5 favors experimental, > 0.5 favors control.\\
     \textsuperscript{\textit{2}}Approximate hazard ratio to cross bound.\\
     \textsuperscript{\textit{3}}wAHR is the weighted AHR.\\
     \textsuperscript{\textit{4}}Cumulative alpha for final analysis (-Inf) is less than the full alpha (0.025) when the futility bound is non-binding. The smaller value subtracts the probability of crossing a futility bound before crossing an efficacy bound at a later analysis (0.025 - Inf = -Inf) under the null hypothesis.\\
@@ -437,8 +429,7 @@
     \bottomrule
     \end{longtable}
     \begin{minipage}{\linewidth}
-    \textsuperscript{\textit{1}}One-sided p-value for experimental vs control treatment.
-              Value < 0.5 favors experimental, > 0.5 favors control.\\
+    \textsuperscript{\textit{1}}One-sided p-value for experimental vs control treatment. Value < 0.5 favors experimental, > 0.5 favors control.\\
     \textsuperscript{\textit{2}}Approximate hazard ratio to cross bound.\\
     \textsuperscript{\textit{3}}wAHR is the weighted AHR.\\
     \end{minipage}
@@ -476,8 +467,7 @@
     \bottomrule
     \end{longtable}
     \begin{minipage}{\linewidth}
-    \textsuperscript{\textit{1}}One-sided p-value for experimental vs control treatment.
-              Value < 0.5 favors experimental, > 0.5 favors control.\\
+    \textsuperscript{\textit{1}}One-sided p-value for experimental vs control treatment. Value < 0.5 favors experimental, > 0.5 favors control.\\
     \textsuperscript{\textit{2}}wAHR is the weighted AHR.\\
     \end{minipage}
     \endgroup
diff --git a/tests/testthat/test-independent-fixed_design.R b/tests/testthat/test-independent-fixed_design.R
index 25794cdf..848c655c 100644
--- a/tests/testthat/test-independent-fixed_design.R
+++ b/tests/testthat/test-independent-fixed_design.R
@@ -138,7 +138,7 @@ test_that("MaxCombo", {
     tau = c(-1, 4, 6)
   )
 
-  expect_equal(y$analysis$power, 0.9, tolerance = testthat_tolerance() * 1000)
+  expect_equal(y$analysis$power, 0.9, tolerance = 1e-4)
 })
 
 test_that("RMST", {