Merge branch 'dev'

DESCRIPTION

@@ -1,7 +1,7 @@
 Package: adaptr
 Title: Adaptive Trial Simulator
-Version: 1.3.1
-Date: 2023-05-02
+Version: 1.3.2
+Date: 2023-08-21
 Authors@R: 
     c(person("Anders", "Granholm",
              email = "andersgran@gmail.com",

NEWS.md

@@ -1,3 +1,25 @@
+# adaptr 1.3.2
+
+This is a patch release with bug fixes and documentation updates.
+
+*   Fixed a bug in `check_performance()` that caused the proportion of
+    conclusive trial simulations (`prob_conclusive`) to be calculated
+    incorrectly when restricted to simulations ending in superiority or with a
+    selected arm according to the selection strategy used in `restrict`. This
+    bug also affected the `summary()` method for multiple simulations (as this
+    relies on `check_performance()`).
+
+*   Fixed a bug in `plot_convergence()` that caused arm selection probabilities
+    to be incorrectly calculated and plotted (this bug did not affect any of the
+    other functions for calculating and summarising simulation results).
+
+*   Corrections to `plot_convergence()` and `summary()` method documentation for
+    arm selection probability extraction.
+
+*   Fixed inconsistency between argument names and documentation in the internal
+    `%f|%` function (renamed arguments for consistency with the internal `%||%`
+    function).
+
 # adaptr 1.3.1
 
 This is a patch release triggered by a CRAN request to fix a failing test that

R/check_performance.R

@@ -246,7 +246,7 @@ check_performance <- function(object, select_strategy = "control if available",
                summarise_num(extr_res$final_n[restrict_idx]),
                summarise_num(extr_res$sum_ys[restrict_idx]),
                summarise_num(extr_res$ratio_ys[restrict_idx]),
-               mean(extr_res$final_status != "max"),
+               mean(extr_res$final_status[restrict_idx] != "max"),
                mean(extr_res$final_status[restrict_idx] == "superiority"),
                mean(extr_res$final_status[restrict_idx] == "equivalence"),
                mean(extr_res$final_status[restrict_idx] == "futility"),
@@ -300,7 +300,7 @@ check_performance <- function(object, select_strategy = "control if available",
                            summarise_num(extr_boot$final_n[restrict_idx]),
                            summarise_num(extr_boot$sum_ys[restrict_idx]),
                            summarise_num(extr_boot$ratio_ys[restrict_idx]),
-                           mean(extr_boot$final_status != "max"),
+                           mean(extr_boot$final_status[restrict_idx] != "max"),
                            mean(extr_boot$final_status[restrict_idx] == "superiority"),
                            mean(extr_boot$final_status[restrict_idx] == "equivalence"),
                            mean(extr_boot$final_status[restrict_idx] == "futility"),

R/plot_convergence.R

@@ -17,9 +17,10 @@
 #'   `ratio_ys_mean`, `ratio_ys_sd`, `ratio_ys_median`, `ratio_ys_p25`,
 #'   `ratio_ys_p75`, `ratio_ys_p0`, `ratio_ys_p100`, `prob_conclusive`,
 #'   `prob_superior`, `prob_equivalence`, `prob_futility`, `prob_max`,
-#'   `prob_select_*` (with `*` being an `arm` name), `rmse`, `rmse_te`, and
-#'   `idp`. All may be specified as above, case sensitive, but with either
-#'   spaces or underlines. Defaults to `"size mean"`.
+#'   `prob_select_*` (with `*` being either "`arm_<name>` for all `arm` names or
+#'   `none`), `rmse`, `rmse_te`, and `idp`. All may be specified as above,
+#'   case sensitive, but with either spaces or underlines. Defaults to
+#'   `"size mean"`.
 #' @param resolution single positive integer, the number of points calculated
 #'   and plotted, defaults to `100` and must be `>= 10`. Higher numbers lead to
 #'   smoother plots, but increases computation time. If the value specified is
@@ -154,7 +155,7 @@ plot_convergence <- function(object, metrics = "size mean", resolution = 100,
     # Get current function
     if (substr(cur_metric, 1, 16) == "prob_select_arm_") {
       cur_arm <- substr(cur_metric, 17, nchar(cur_metric))
-      cur_fun <- function(i) sum(extr_res$selected_arm[start_id:i] == cur_arm, na.rm = TRUE) / n_restrict  * 100
+      cur_fun <- function(i) sum(extr_res$selected_arm[start_id:i] == cur_arm, na.rm = TRUE) / length(start_id:i)  * 100
     } else {
       cur_fun <- switch(cur_metric,
                         size_mean = function(i) mean(extr_res$final_n[start_id:i]),

R/summary.R

@@ -22,11 +22,12 @@
 #'     `ratio_ys_sd`, `ratio_ys_median`, `ratio_ys_p25`, `ratio_ys_p75`,
 #'     `ratio_ys_p0`, `ratio_ys_p100`, `prob_conclusive`, `prob_superior`,
 #'     `prob_equivalence`, `prob_futility`, `prob_max`, `prob_select_*` (with
-#'     `*` being all `arm` names), `rmse`, `rmse_te`, and `idp`: performance
-#'     metrics as described in [check_performance()]. Note that all `sum_ys_`
-#'     and `ratio_ys_` measures uses outcome data from all randomised patients,
-#'    regardless of whether they had outcome data available at the last analysis
-#'    or not, as described in [extract_results()].
+#'     `*` being either "`arm_<name>` for all `arm` names or `none`), `rmse`,
+#'     `rmse_te`, and `idp`: performance metrics as described in
+#'     [check_performance()]. Note that all `sum_ys_` and `ratio_ys_` measures
+#'     use outcome data from all randomised patients, regardless of whether they
+#'     had outcome data available at the last analysis or not, as described in
+#'     [extract_results()].
 #'   \item `select_strategy`, `select_last_arm`, `select_preferences`,
 #'     `te_comp`, `raw_ests`, `final_ests`, `restrict`: as specified above.
 #'   \item `control`: the control arm specified by [setup_trial()],

R/utils.R

@@ -212,9 +212,9 @@ verify_int <- function(x, min_value = -Inf, max_value = Inf, open = "no") {
 #'
 #' @name replace_nonfinite
 #'
-`%f|%` <- function(x, y) {
-  x[!is.finite(x)] <- y
-  x
+`%f|%` <- function(a, b) {
+  a[!is.finite(a)] <- b
+  a
 }
 
 

README.md

@@ -66,7 +66,7 @@ general `setup_trial()` function, or one of the special case functions,
 
 ``` r
 library(adaptr)
-#> Loading 'adaptr' package v1.3.1.
+#> Loading 'adaptr' package v1.3.2.
 #> For instructions, type 'help("adaptr")'
 #> or see https://inceptdk.github.io/adaptr/.
 
@@ -210,7 +210,7 @@ print(res_sum, digits = 1)
 #> * Ideal design percentage: 100.0%
 #> 
 #> Simulation details:
-#> * Simulation time: 0.622 secs
+#> * Simulation time: 0.475 secs
 #> * Base random seed: 67890
 #> * Credible interval width: 95%
 #> * Number of posterior draws: 5000

cran-comments.md

@@ -1,7 +1,6 @@
 ## Release summary
 
-This is a patch release triggered by a CRAN request to fix a failing test on R
-patched that also includes minor documentation updates.
+This is a patch release with bug fixes and documentation updates.
 
 ## R CMD check results
 

tests/testthat/_snaps/check_performance.md

@@ -195,7 +195,7 @@
       20      ratio_ys_p75    0.228
       21       ratio_ys_p0    0.216
       22     ratio_ys_p100    0.270
-      23   prob_conclusive    0.800
+      23   prob_conclusive    1.000
       24     prob_superior    1.000
       25  prob_equivalence    0.000
       26     prob_futility    0.000
@@ -236,7 +236,7 @@
       20      ratio_ys_p75    0.228
       21       ratio_ys_p0    0.216
       22     ratio_ys_p100    0.270
-      23   prob_conclusive    0.800
+      23   prob_conclusive    1.000
       24     prob_superior    1.000
       25  prob_equivalence    0.000
       26     prob_futility    0.000
@@ -280,7 +280,7 @@
       20      ratio_ys_p75    0.228   0.008   0.004    0.222    0.253
       21       ratio_ys_p0    0.216      NA      NA       NA       NA
       22     ratio_ys_p100    0.270      NA      NA       NA       NA
-      23   prob_conclusive    0.800   0.086   0.074    0.650    0.950
+      23   prob_conclusive    1.000   0.000   0.000    1.000    1.000
       24     prob_superior    1.000   0.000   0.000    1.000    1.000
       25  prob_equivalence    0.000   0.000   0.000    0.000    0.000
       26     prob_futility    0.000   0.000   0.000    0.000    0.000
@@ -324,7 +324,7 @@
       20      ratio_ys_p75    0.228   0.008   0.004    0.222    0.253
       21       ratio_ys_p0    0.216      NA      NA       NA       NA
       22     ratio_ys_p100    0.270      NA      NA       NA       NA
-      23   prob_conclusive    0.800   0.086   0.074    0.650    0.950
+      23   prob_conclusive    1.000   0.000   0.000    1.000    1.000
       24     prob_superior    1.000   0.000   0.000    1.000    1.000
       25  prob_equivalence    0.000   0.000   0.000    0.000    0.000
       26     prob_futility    0.000   0.000   0.000    0.000    0.000

tests/testthat/_snaps/summary-print.md

@@ -146,7 +146,7 @@
       * Ideal design percentage: 100.0%
       
       Simulation details:
-      * Simulation time: 0.829 secs
+      * Simulation time: 0.73 secs
       * Base random seed: 12345
       * Credible interval width: 95%
       * Number of posterior draws: 5000
@@ -180,7 +180,7 @@
       * Ideal design percentage: 100.0%
       
       Simulation details:
-      * Simulation time: 0.829 secs
+      * Simulation time: 0.73 secs
       * Base random seed: 12345
       * Credible interval width: 95%
       * Number of posterior draws: 5000