84 api

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: gsDesign2
 Title: Group Sequential Design with Non-Constant Effect
-Version: 0.2.0.9000
+Version: 0.2.0.9001
 Authors@R: c(
     person("Keaven", "Anderson", email = "keaven_anderson@merck.com", role = c("aut")),
     person("Yilong", "Zhang", email = "elong0527@gmail.com", role = c("aut")),

NAMESPACE

@@ -6,8 +6,9 @@ S3method(summary,fixed_design)
 S3method(summary,gs_design)
 export(AHR)
 export(as_gt)
-export(eAccrual)
-export(eEvents_df)
+export(expected_accrual)
+export(expected_event)
+export(expected_time)
 export(fixed_design)
 export(gs_b)
 export(gs_design_ahr)
@@ -29,7 +30,6 @@ export(gs_spending_combo)
 export(pmvnorm_combo)
 export(ppwe)
 export(s2pwe)
-export(tEvents)
 export(wlr_weight_1)
 export(wlr_weight_fh)
 export(wlr_weight_n)

R/AHR.R

@@ -26,13 +26,13 @@ NULL
 #' various non-proportional hazards assumptions for either single or multiple strata studies.
 #' The piecewise exponential distribution allows a simple method to specify a distribution
 #' and enrollment pattern where the enrollment, failure and dropout rates changes over time.
-#' @param enrollRates Piecewise constant enrollment rates by stratum and time period.
-#' @param failRates Piecewise constant control group failure rates, duration for each piecewise constant period,
+#' @param enroll_rate Piecewise constant enrollment rates by stratum and time period.
+#' @param fail_rate Piecewise constant control group failure rates, duration for each piecewise constant period,
 #' hazard ratio for experimental vs control, and dropout rates by stratum and time period.
-#' @param totalDuration Total follow-up from start of enrollment to data cutoff;
+#' @param total_duration Total follow-up from start of enrollment to data cutoff;
 #' this can be a single value or a vector of positive numbers.
 #' @param ratio ratio of experimental to control randomization.
-#' @param simple logical; if TRUE (default), for each value in input totalDuration overall event count,
+#' @param simple logical; if TRUE (default), for each value in input total_duration overall event count,
 #' statistical information and average hazard ratio are given;
 #' if FALSE, hazard ratio, expected events and statistical information are produced by stratum and underlying hazard ratio.
 #' @section Specification:
@@ -63,7 +63,7 @@ NULL
 #'       information under the null and the given scenarios.
 #'       }
 #'    \item Return a tibble of overall event count, statistical information and average hazard ratio
-#'    of each value in totalDuration if the input simple is true, or a tibble of hazard ratio,
+#'    of each value in total_duration if the input simple is true, or a tibble of hazard ratio,
 #'    expected events and statistical information  produced by stratum and
 #'    underlying hazard ratio if the input simple is false.
 #'    \item Calculation of \code{AHR} for different design scenarios, and the comparison to the
@@ -72,55 +72,55 @@ NULL
 #' }
 #' \if{html}{The contents of this section are shown in PDF user manual only.}
 #'
-#' @return A `tibble` with `Time` (from `totalDuration`), `AHR` (average hazard ratio),
+#' @return A `tibble` with `Time` (from `total_duration`), `AHR` (average hazard ratio),
 #' `Events` (expected number of events), info (information under given scenarios),
-#' and info0 (information under related null hypothesis) for each value of `totalDuration` input;
+#' and info0 (information under related null hypothesis) for each value of `total_duration` input;
 #' if `simple=FALSE`, `Stratum` and `t` (beginning of each constant HR period) are also returned
 #' and `HR` is returned instead of `AHR`
 #' 
 #' @examples
 #' # Example: default
 #' AHR()
 #' 
-#' # Example: default with multiple analysis times (varying totalDuration)
+#' # Example: default with multiple analysis times (varying total_duration)
 #' 
-#' AHR(totalDuration = c(15, 30))
+#' AHR(total_duration = c(15, 30))
 #' 
 #' # Stratified population
-#' enrollRates <- tibble::tibble(Stratum = c(rep("Low", 2), rep("High", 3)),
+#' enroll_rate <- tibble::tibble(Stratum = c(rep("Low", 2), rep("High", 3)),
 #'                               duration = c(2, 10, 4, 4, 8),
 #'                               rate = c(5, 10, 0, 3, 6))
-#' failRates <- tibble::tibble(Stratum = c(rep("Low", 2), rep("High", 2)),
+#' fail_rate <- tibble::tibble(Stratum = c(rep("Low", 2), rep("High", 2)),
 #'                             duration = 1,
-#'                             failRate = c(.1, .2, .3, .4),
+#'                             fail_rate = c(.1, .2, .3, .4),
 #'                             hr = c(.9, .75, .8, .6),
-#'                             dropoutRate = .001)
-#' AHR(enrollRates = enrollRates, failRates = failRates, totalDuration = c(15, 30))
+#'                             dropout_rate = .001)
+#' AHR(enroll_rate = enroll_rate, fail_rate = fail_rate, total_duration = c(15, 30))
 #' 
 #' # Same example, give results by strata and time period
-#' AHR(enrollRates = enrollRates, failRates = failRates, totalDuration = c(15, 30), simple = FALSE)
+#' AHR(enroll_rate = enroll_rate, fail_rate = fail_rate, total_duration = c(15, 30), simple = FALSE)
 #' 
 #' @export
 #'
-AHR <- function(enrollRates = tibble::tibble(Stratum = "All",
+AHR <- function(enroll_rate = tibble::tibble(Stratum = "All",
                                              duration = c(2, 2, 10),
                                              rate = c(3, 6, 9)),
-                failRates = tibble::tibble(Stratum = "All",
+                fail_rate = tibble::tibble(Stratum = "All",
                                            duration = c(3, 100),
-                                           failRate = log(2) / c(9, 18),
+                                           fail_rate = log(2) / c(9, 18),
                                            hr = c(.9, .6),
-                                           dropoutRate = rep(.001, 2)),
-                totalDuration = 30,
+                                           dropout_rate = rep(.001, 2)),
+                total_duration = 30,
                 ratio = 1,
                 simple = TRUE
 ){
   # ----------------------------#
   #    check input values       #
   # ----------------------------#
-  check_enrollRates(enrollRates)
-  check_failRates(failRates)
-  check_enrollRates_failRates(enrollRates, failRates)
-  check_totalDuration(totalDuration)
+  check_enroll_rate(enroll_rate)
+  check_fail_rate(fail_rate)
+  check_enroll_rate_fail_rate(enroll_rate, fail_rate)
+  check_total_duration(total_duration)
   check_ratio(ratio)
   if(!is.logical(simple)){stop("gsDesign2: simple in `AHR()` must be logical")}
 
@@ -130,28 +130,28 @@ AHR <- function(enrollRates = tibble::tibble(Stratum = "All",
 
   # compute expected events by treatment group, stratum and time period
   ans <- NULL
-  strata <- unique(enrollRates$Stratum)
+  strata <- unique(enroll_rate$Stratum)
 
-  for(td in totalDuration){
+  for(td in total_duration){
 
     events <- NULL
 
     for(s in strata){
       # subset to stratum
-      enroll <- enrollRates %>% filter(Stratum == s)
-      fail <- failRates %>% filter(Stratum == s)
+      enroll <- enroll_rate %>% filter(Stratum == s)
+      fail <- fail_rate %>% filter(Stratum == s)
 
       # update enrollment rates
       enroll_c <- enroll %>% mutate(rate = rate * Qc)
       enroll_e <- enroll %>% mutate(rate = rate * Qe)
 
       # update failure rates
       fail_c <- fail
-      fail_e <- fail %>% mutate(failRate = failRate * hr)
+      fail_e <- fail %>% mutate(fail_rate = fail_rate * hr)
 
       # compute expected number of events
-      events_c <- eEvents_df(enrollRates = enroll_c, failRates = fail_c, totalDuration = td, simple = FALSE)
-      events_e <- eEvents_df(enrollRates = enroll_e, failRates = fail_e, totalDuration = td, simple = FALSE)
+      events_c <- expected_event(enroll_rate = enroll_c, fail_rate = fail_c, total_duration = td, simple = FALSE)
+      events_e <- expected_event(enroll_rate = enroll_e, fail_rate = fail_e, total_duration = td, simple = FALSE)
 
       # Combine control and experimental; by period recompute HR, events, information
       events <- rbind(events_c %>% mutate(Treatment = "Control"),

R/as_gt.R

@@ -47,21 +47,21 @@ as_gt <- function(x, ...) {
 #' library(tibble)
 #' 
 #' # Enrollment rate
-#' enrollRates <- tibble(
+#' enroll_rate <- tibble(
 #'   Stratum = "All", 
 #'   duration = 18, 
 #'   rate = 20)
 #' 
 #' # Failure rates
-#' failRates <- tibble(
+#' fail_rate <- tibble(
 #'   Stratum = "All", 
 #'   duration = c(4, 100), 
-#'   failRate = log(2) / 12,
+#'   fail_rate = log(2) / 12,
 #'   hr = c(1, .6), 
-#'   dropoutRate = .001)
+#'   dropout_rate = .001)
 #' 
 #' # Study duration in months
-#' studyDuration <- 36
+#' study_duration <- 36
 #' 
 #' # Experimental / Control randomization ratio
 #' ratio <- 1 
@@ -79,8 +79,8 @@ as_gt <- function(x, ...) {
 #' fixed_design(
 #'   x = "AHR", 
 #'   alpha = alpha, power = 1 - beta, 
-#'   enrollRates = enrollRates, failRates = failRates, 
-#'   studyDuration = studyDuration, ratio = ratio
+#'   enroll_rate = enroll_rate, fail_rate = fail_rate, 
+#'   study_duration = study_duration, ratio = ratio
 #'   ) %>% 
 #'   summary() %>% 
 #'   as_gt()
@@ -90,71 +90,71 @@ as_gt <- function(x, ...) {
 #' # ------------------------- #
 #' # under fixed power
 #' fixed_design(
-#'   x = "FH", 
+#'   "fh", 
 #'   alpha = alpha, power = 1 - beta, 
-#'   enrollRates = enrollRates, failRates = failRates, 
-#'   studyDuration = studyDuration, ratio = ratio
+#'   enroll_rate = enroll_rate, fail_rate = fail_rate,
+#'   study_duration = study_duration, ratio = ratio
 #'   ) %>% 
 #'   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"
+  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 Max Combo Method"},
-                     "Milestone" = {"Fixed Design under Milestone Method"},
-                     "RMST" = {"Fixed Design under Restricted Mean Survival Time Method"},
-                     "RD" = {"Fixed Design of Risk Difference"}
+                     "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 Max Combo Method"},
+                     "milestone" = {"Fixed Design under Milestone Method"},
+                     "rmst" = {"Fixed Design under Restricted Mean Survival Time Method"},
+                     "rd" = {"Fixed Design of Risk Difference"}
     )
   }
 
 
   # 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 ",
+                        "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 ",
+                        "mb" = {paste0("Power for ",
                                        x$Design,
                                        " computed with method of Yung and Liu.")},
-                        "LF" = {"Power using Lachin and Foulkes method applied using expected average hazard ratio (AHR) at time of planned analysis."},
-                        "RD" = {"Risk difference power without continuity correction using method of Farrington and Manning."},
-                        "MaxCombo" = {paste0("Power for MaxCombo test with Fleming-Harrington tests",
+                        "lf" = {"Power using Lachin and Foulkes method applied using expected average hazard ratio (AHR) at time of planned analysis."},
+                        "rd" = {"Risk difference power without continuity correction using method of Farrington and Manning."},
+                        "maxcombo" = {paste0("Power for MaxCombo test with Fleming-Harrington tests",
                                              substr(x$Design, 9, nchar(x$Design)), "."
                                              # paste(apply(do.call(rbind, x$design_par), 2 , paste , collapse = "," ), collapse = ") and ("),
                         )},
-                        "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.")}
+                        "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.")}
     )  
   }