Use data.table for grouped sort in pw_info()

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: gsDesign2
 Title: Group Sequential Design with Non-Constant Effect
-Version: 1.1.0.1
+Version: 1.1.0.2
 Authors@R: c(
     person("Keaven", "Anderson", email = "[email protected]", role = c("aut")),
     person("Yilong", "Zhang", email = "[email protected]", role = c("aut")),

NAMESPACE

@@ -59,6 +59,7 @@ importFrom(data.table,last)
 importFrom(data.table,rbindlist)
 importFrom(data.table,setDF)
 importFrom(data.table,setDT)
+importFrom(data.table,setorderv)
 importFrom(dplyr,"%>%")
 importFrom(dplyr,all_of)
 importFrom(dplyr,arrange)

R/globals.R

@@ -20,7 +20,7 @@ utils::globalVariables(
   unique(
     c(
       # From data.table expressions
-      ".",
+      ".", ".SD",
       # From `ahr()`
       c("stratum", "rate", "hr", "treatment", "time", "info0", "info"),
       # From `as_gt.gs_design()`

R/gs_info_ahr.R

@@ -29,7 +29,7 @@
 #' @param interval An interval that is presumed to include the time at which
 #'   expected event count is equal to targeted event.
 #'
-#' @return A tibble with columns Analysis, Time, AHR, Events, theta, info, info0.
+#' @return A data frame with columns Analysis, Time, AHR, Events, theta, info, info0.
 #'   `info`, and `info0` contain statistical information under H1, H0, respectively.
 #'   For analysis `k`, `Time[k]` is the maximum of `analysis_time[k]` and the
 #'   expected time required to accrue the targeted `event[k]`.
@@ -46,7 +46,7 @@
 #'      \item If analysis_time is specified, calculate average hazard ratio using \code{AHR()}.
 #'      \item If event is specified, calculate average hazard ratio using \code{expected_time()}.
 #'    }
-#'    \item Return a tibble of Analysis, Time, AHR, Events, theta, info, info0.
+#'    \item Return a data frame of Analysis, Time, AHR, Events, theta, info, info0.
 #'   }
 #' }
 #' \if{html}{The contents of this section are shown in PDF user manual only.}
@@ -56,8 +56,6 @@
 #' event times. The [expected_time()] function is used to get events and
 #' average HR at targeted `analysis_time`.
 #'
-#' @importFrom tibble tibble
-#'
 #' @export
 #'
 #' @examples
@@ -172,6 +170,6 @@ gs_info_ahr <- function(
   # ----------------------------#
   #    output results           #
   # ----------------------------#
-  ans <- avehr %>% dplyr::transmute(analysis, time, event, ahr, theta, info, info0)
+  ans <- avehr[, c("analysis", "time", "event", "ahr", "theta", "info", "info0")]
   return(ans)
 }

R/gs_info_rd.R

@@ -32,6 +32,7 @@
 #'   theta0 (standardized treatment effect under null hypothesis),
 #'   and statistical information.
 #'
+#' @importFrom dplyr group_by left_join mutate select summarize ungroup
 #'
 #' @export
 #'

R/pw_info.R

@@ -73,7 +73,7 @@
 #' \if{html}{The contents of this section are shown in PDF user manual only.}
 #'
 #' @importFrom data.table ":=" as.data.table copy first last rbindlist setDF
-#' @importFrom dplyr group_by summarize ungroup "%>%"
+#'                        setorderv
 #'
 #' @export
 #'
@@ -204,10 +204,8 @@ pw_info <- function(
   ans <- rbindlist(ans_list)
   # output the results
   ans <- ans[, .(time, stratum, t, hr, event, info, info0)]
-  ans <- ans %>%
-    group_by(time, stratum) %>%
-    arrange(t, .by_group = TRUE) %>%
-    ungroup()
+  setorderv(ans, cols = c("time", "stratum"))
+  ans <- ans[order(t), .SD, by = .(time, stratum)]
   setDF(ans)
   return(ans)
 }