Merge pull request #49 from mattheaphy/dev-cli

Development version - control variables and CLI updates

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: actxps
 Title: Create Actuarial Experience Studies: Prepare Data, Summarize Results, and Create Reports
-Version: 1.5.0
+Version: 1.5.0.9000
 Authors@R: 
     person("Matt", "Heaphy", email = "mattrmattrs@gmail.com", role = c("aut", "cre"))
 Maintainer: Matt Heaphy <mattrmattrs@gmail.com>
@@ -20,7 +20,7 @@ URL: https://github.com/mattheaphy/actxps/,
 BugReports: https://github.com/mattheaphy/actxps/issues
 Encoding: UTF-8
 Roxygen: list(markdown = TRUE)
-RoxygenNote: 7.3.0
+RoxygenNote: 7.3.2
 Suggests: 
     knitr,
     RColorBrewer,
@@ -47,6 +47,7 @@ Imports:
     readr,
     tidyr,
     vctrs,
-    clock
+    clock,
+    cli
 LazyData: true
 VignetteBuilder: knitr

NEWS.md

@@ -1,3 +1,22 @@
+# actxps (development version)
+
+- New feature - control variables
+
+  - `exp_stats()` has two new arguments: `control_vars` and 
+    `control_distinct_max`.
+  - Control variables are used to estimate the impact of any grouping variables 
+    on observed experience after accounting for the impact of control 
+    variables. The idea here is that experience is first summarized across the
+    control variables to derive a new expected values basis. This expected
+    values basis is then used to calculate actual-to-expected ratios.
+  - The `control_distinct_max` argument places an upper limit on the maximum
+    number of unique values allowed in any control variable.
+  - `exp_shiny()` now includes a control variable selection widget.
+
+- Added the "cli" package to replace "rlang" for certain errors, warnings, and 
+  messages.
+- Various small typo fixes.
+
 # actxps 1.5.0
 
 - `expose_split()` bug fixes: 

R/exp_df_helpers.R

@@ -149,7 +149,8 @@ as_exp_df <- function(x, expected = NULL, wt = NULL,
              wt = wt,
              credibility = credibility,
              conf_level = conf_level, cred_r = cred_r,
-             conf_int = conf_int)
+             conf_int = conf_int,
+             control_vars = NULL)
 
 }
 

R/exp_shiny.R

@@ -49,11 +49,13 @@
 #' #### Termination studies
 #'
 #' The expected values checkboxes are used to activate and deactivate expected
-#' values passed to the `expected` argument. This impacts the table output
-#' directly and the available "y" variables for the plot. If there are no
-#' expected values available, this widget will not appear. The "Weight by"
-#' widget is used to specify which column, if any, contains weights for
-#' summarizing experience.
+#' values passed to the `expected` argument. These checkboxes also include a
+#' a "control" item for expected values derived using control variables.
+#' These boxes impact the table output directly and the available "y" variables
+#' for the plot. The "Weight by" widget is used to specify which column, if any,
+#' contains weights for summarizing experience. The "Control variables" widget
+#' is used to specify which columns, if any, are used as control variables (
+#' see [exp_stats()] for more information).
 #'
 #' #### Transaction studies
 #'
@@ -265,8 +267,8 @@ exp_shiny <- function(dat,
     choices <- info$scope[[1]]
 
     if (is.null(dat[[x]])) {
-      rlang::abort(
-        glue::glue("Error creating an input widget for {x}. {x} does not exist in the input data.")
+      cli::cli_abort(
+        "Error creating an input widget for {x}. {x} does not exist in the input data."
       )
     }
 
@@ -309,8 +311,8 @@ exp_shiny <- function(dat,
 
     } else {
 
-      rlang::abort(
-        glue::glue("Error creating an input widget for {x}. {x} is of class {class(dat[[x]]) |> paste(collapse = ', ')}, which is not supported.")
+      cli::cli_abort(
+        "Error creating an input widget for {x}. {x} is of class {class(dat[[x]])}, which is not supported."
       )
 
     }
@@ -355,18 +357,10 @@ exp_shiny <- function(dat,
   }
 
   # expected values set up
-  if (length(expected) > 0) {
-
-    has_expected <- TRUE
-
-    expected_widget <- checkboxGroupPred("ex_checks", "Expected values:", 6,
-                                         choices = expected,
-                                         selected = expected)
-
-  } else {
-    has_expected <- FALSE
-    expected_widget <- NULL
-  }
+  expected <- c(expected, "control")
+  expected_widget <- checkboxGroupPred(
+    "ex_checks", "Expected values:", 4,
+    choices = expected, selected = expected[expected != "control"])
 
   # transactions set up
   if (has_trx) {
@@ -506,9 +500,12 @@ exp_shiny <- function(dat,
           value = "exp",
           shiny::fluidRow(
             expected_widget,
-            selectPred("weightVar", "Weight by:", 6,
+            selectPred("weightVar", "Weight by:", 4,
                        choices = c("None",
-                                   filter(preds, is_number)$predictors))
+                                   filter(preds, is_number)$predictors)),
+            selectPred("controlVars", "Control variables:", 4,
+                       multiple = TRUE,
+                       choices = preds_small)
           )),
 
         trx_tab
@@ -528,16 +525,16 @@ exp_shiny <- function(dat,
               shiny::markdown(
                 '<div style="text-align: left">
 
-                - `y`-axis variable selection
-                - `Second y-axis` toggle and variable
-                - `Geometry` for plotting
-                - `Add smoothing`: add smooth loess curves
-                - `Confidence intervals`: If available, draw confidence interval
-                error bars
-                - `Free y-scales`: enable separate `y` scales in each subplot
-                - `Log y-axis`: plot y-axes on a log-10 scale
-                - The grouping variables selected above will determine the
-                  variable on the `x`-axis, the color variable, and faceting
+                - **y-axis** variable selection
+                - **Second y-axis** toggle and variable
+                - **Geometry** for plotting
+                - **Add smoothing**: add smooth loess curves
+                - **Confidence intervals**: If available, draw confidence
+                interval error bars
+                - **Free y-scales**: enable separate y scales in each subplot
+                - **Log y-axis**: plot y-axes on a log-10 scale
+                - The **grouping variables** selected above will determine the
+                  variable on the x-axis, the color variable, and faceting
                   variables used to create subplots.
 
                 </div>'),
@@ -806,16 +803,17 @@ exp_shiny <- function(dat,
         }
       }
 
-      ex <- if (has_expected) {
-        input$ex_checks
+      ex <- input$ex_checks[input$ex_checks != "control"]
+      ctrl <- if ("control" %in% input$ex_checks) {
+        input$controlVars %||% ".none"
       }
 
       if (input$study_type == "exp") {
         rdat() |>
           group_by(dplyr::across(dplyr::all_of(.groups))) |>
           exp_stats(wt = wt, credibility = credibility, expected = ex,
                     conf_level = conf_level, cred_r = cred_r,
-                    conf_int = TRUE)
+                    conf_int = TRUE, control_vars = ctrl)
       } else {
         rdat() |>
           group_by(dplyr::across(dplyr::all_of(.groups))) |>