Merge pull request #66 from rpact-com/dev/4.1.1

Enhancement #65 and other improvements
rpact-com · Nov 20, 2024 · ae013d3 · ae013d3
2 parents d0eecb9 + 24c9a98
commit ae013d3
Show file tree

Hide file tree

Showing 53 changed files with 958 additions and 709 deletions.
diff --git a/DESCRIPTION b/DESCRIPTION
@@ -1,7 +1,7 @@
 Package: rpact
 Title: Confirmatory Adaptive Clinical Trial Design and Analysis
-Version: 4.1.0.9268
-Date: 2024-11-07
+Version: 4.1.0.9271
+Date: 2024-11-20
 Authors@R: c(
 	person(
 		given = "Gernot", 
@@ -103,6 +103,7 @@ Collate:
     'f_analysis_base_means.R'
     'f_analysis_base_rates.R'
     'f_analysis_base_survival.R'
+    'f_analysis_boundary_recalculation.R'
     'f_analysis_enrichment.R'
     'f_analysis_enrichment_means.R'
     'f_analysis_enrichment_rates.R'

diff --git a/NEWS.md b/NEWS.md
@@ -6,7 +6,14 @@
 
 ## Improvements, issues, and changes
 
+* The full set of unit tests for rpact is now stored in a private repository. 
+  Only members of the 'RPACT User Group' have access to the tests.
+  For more information, please visit: [rpact.org/iq](www.rpact.org/iq)
+* Usage of `maxInformation` improved (see enhancement [#65](https://github.com/rpact-com/rpact/issues/65))
+* `testPackage()`: additional warning details will be added to the test report if warnings exist
 * Issue [#61](https://github.com/rpact-com/rpact/issues/61)) fixed
+* Flexibility of function `getPiecewiseSurvivalTime()` improved
+* Test coverage improved
 * Minor improvements
 
 

diff --git a/R/class_core_parameter_set.R b/R/class_core_parameter_set.R
@@ -13,8 +13,8 @@
 ## |
 ## |  Contact us for information about our services: info@rpact.com
 ## |
-## |  File version: $Revision: 8274 $
-## |  Last changed: $Date: 2024-09-26 11:33:59 +0200 (Do, 26 Sep 2024) $
+## |  File version: $Revision: 8416 $
+## |  Last changed: $Date: 2024-11-18 16:13:44 +0100 (Mo, 18 Nov 2024) $
 ## |  Last changed by: $Author: pahlke $
 ## |
 
@@ -285,6 +285,9 @@ ParameterSet <- R6::R6Class("ParameterSet",
         isUndefinedParameter = function(parameterName) {
             return(self$.getParameterType(parameterName) == C_PARAM_TYPE_UNKNOWN)
         },
+        isNotApplicableParameter = function(parameterName) {
+            return(self$.getParameterType(parameterName) == C_PARAM_NOT_APPLICABLE)
+        },
         .getInputParameters = function() {
             params <- self$.getParametersOfOneGroup(c(C_PARAM_USER_DEFINED, C_PARAM_DEFAULT_VALUE))
             return(params)
@@ -1323,7 +1326,7 @@ ParameterSet <- R6::R6Class("ParameterSet",
         parametersToIgnore <- intersect(parametersToIgnore, parameterNames)
     }
 
-    if (parameterSet$.getParameterType("hazardRatio") == C_PARAM_GENERATED &&
+    if (parameterSet$isGeneratedParameter("hazardRatio") &&
             !is.null(parameterSet[[".piecewiseSurvivalTime"]]) &&
             isTRUE(parameterSet$.piecewiseSurvivalTime$piecewiseSurvivalEnabled)) {
         parametersToIgnore <- c(parametersToIgnore, "hazardRatio")

diff --git a/R/class_design.R b/R/class_design.R
@@ -13,8 +13,8 @@
 ## |
 ## |  Contact us for information about our services: info@rpact.com
 ## |
-## |  File version: $Revision: 8180 $
-## |  Last changed: $Date: 2024-09-06 10:13:14 +0200 (Fr, 06 Sep 2024) $
+## |  File version: $Revision: 8416 $
+## |  Last changed: $Date: 2024-11-18 16:13:44 +0100 (Mo, 18 Nov 2024) $
 ## |  Last changed by: $Author: pahlke $
 ## |
 
@@ -736,7 +736,7 @@ TrialDesignInverseNormal <- R6::R6Class("TrialDesignInverseNormal",
                     informationRatesTemp, self$informationRates
                 ))
             }
-            if (self$.getParameterType("futilityBounds") != C_PARAM_GENERATED &&
+            if (!self$isGeneratedParameter("futilityBounds") &&
                     (!grepl("^as.*", typeOfDesign) || typeBetaSpending == C_TYPE_OF_DESIGN_BS_NONE) &&
                     !identical(futilityBoundsTemp, self$futilityBounds)) {
                 return(self$.pasteComparisonResult(
@@ -953,10 +953,14 @@ TrialDesignConditionalDunnett <- R6::R6Class("TrialDesignConditionalDunnett",
         informationAtInterim = NULL,
         secondStageConditioning = NULL,
         sided = NULL,
-        initialize = function(..., informationAtInterim = NULL, secondStageConditioning = NULL) {
+        initialize = function(..., 
+                informationAtInterim = NULL, 
+                secondStageConditioning = NULL,
+                directionUpper = NA) {
             super$initialize(...)
             self$informationAtInterim <- informationAtInterim
             self$secondStageConditioning <- secondStageConditioning
+            self$directionUpper <- directionUpper
             notApplicableParameters <- c(
                 "kMax",
                 "stages",
@@ -1009,6 +1013,8 @@ TrialDesignConditionalDunnett <- R6::R6Class("TrialDesignConditionalDunnett",
 #'        If \code{secondStageConditioning = FALSE} is specified, the unconditional adjusted p-values are used, otherwise
 #'  	  conditional adjusted p-values are calculated, default is \code{secondStageConditioning = TRUE}
 #'        (for details, see Koenig et al., 2008).
+#' @inheritParams param_directionUpper
+#' @inheritParams param_three_dots
 #'
 #' @details
 #' For performing the conditional Dunnett test the design must be defined through this function.
@@ -1025,16 +1031,25 @@ TrialDesignConditionalDunnett <- R6::R6Class("TrialDesignConditionalDunnett",
 #'
 #' @export
 #'
-getDesignConditionalDunnett <- function(alpha = 0.025, # C_ALPHA_DEFAULT
-        informationAtInterim = 0.5, secondStageConditioning = TRUE) {
+getDesignConditionalDunnett <- function(
+        alpha = 0.025, # C_ALPHA_DEFAULT
+        informationAtInterim = 0.5,
+        ..., 
+        secondStageConditioning = TRUE,
+        directionUpper = NA) {
     .assertIsValidAlpha(alpha)
     .assertIsSingleNumber(informationAtInterim, "informationAtInterim")
     .assertIsInOpenInterval(informationAtInterim, "informationAtInterim", 0, 1)
-    return(TrialDesignConditionalDunnett$new(
+    .assertIsSingleLogical(directionUpper, "directionUpper", naAllowed = TRUE)
+    design <- TrialDesignConditionalDunnett$new(
         alpha = alpha,
         informationAtInterim = informationAtInterim,
-        secondStageConditioning = secondStageConditioning
-    ))
+        secondStageConditioning = secondStageConditioning,
+        directionUpper = directionUpper
+    )
+    design$.setParameterType("directionUpper", ifelse(!is.na(directionUpper), 
+        C_PARAM_USER_DEFINED, C_PARAM_NOT_APPLICABLE))
+    return(design)
 }
 
 #'