Merge pull request #320 from insightsengineering/cran-release

Cran release

.Rbuildignore

@@ -12,4 +12,7 @@
 ^docs$
 ^pkgdown$
 ^data-raw$
+^.DS_Store$
 
+^CRAN-SUBMISSION$
+^cran-comments\.md$

.github/workflows/check_nightly_cran.yaml → .github/workflows/on_nightly_cran.yaml

@@ -4,7 +4,7 @@ on:
   schedule:
     - cron: '0 4 * * 1'
 
-name: Check Nightly (CRAN)
+name: On Nightly (CRAN)
 
 jobs:
 

.github/workflows/check_nightly_main.yaml → .github/workflows/on_nightly_main.yaml

@@ -4,7 +4,7 @@ on:
   schedule:
     - cron: '0 4 * * 1,2,3,4,5'
 
-name: Check Nightly (Main)
+name: On Nightly (Main)
 
 jobs:
 

.github/workflows/check_pr.yaml → .github/workflows/on_pr.yaml

@@ -5,7 +5,7 @@ on:
     paths-ignore:
       - 'misc/**'
 
-name: Check Pull Requests
+name: On Pull Request
 
 jobs:
 
@@ -36,10 +36,26 @@ jobs:
       - name: Build src
         uses: ./.github/actions/build-src
 
-
       - name: Check
         run: |
           options(crayon.enabled = TRUE)
           rcmdcheck::rcmdcheck(args = c("--no-manual", "--as-cran"), error_on = "warning")
         shell: Rscript {0}
-
+
+
+  vignettes:
+    strategy:
+      fail-fast: true
+      matrix:
+       config:
+         - { image: "ghcr.io/${{ github.repository_owner }}/rbmi:r404"}
+         - { image: "ghcr.io/${{ github.repository_owner }}/rbmi:r410"}
+    runs-on: ubuntu-latest
+    container:
+      image: ${{ matrix.config.image }}
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v2
+      - name: testthat
+        run: |
+          Rscript ./vignettes/build.R

.github/workflows/check_pr_cran.yaml → .github/workflows/on_pr_cran.yaml

@@ -7,7 +7,7 @@ on:
     branches:
       - cran
 
-name: Check Pull Requests (CRAN)
+name: On Pull Request CRAN
 
 jobs:
 

.gitignore

@@ -48,6 +48,7 @@ po/*~
 src/*
 
 .DS_store
+.DS_Store
 
 nul
 

DESCRIPTION

@@ -7,7 +7,7 @@ Authors@R: c(
     person("Marcel", "Wolbers", email = "[email protected]", role = "ctb"),
     person("Roche", role = c("cph", "fnd"))
     )
-Description: Implements reference based multiple imputation allowing for the imputation of longditudinal datasets using pre-defined strategies.
+Description: Implements reference based multiple imputation allowing for the imputation of longitudinal datasets using pre-defined strategies.
 Encoding: UTF-8
 LazyData: true
 Roxygen: list(markdown = TRUE)
@@ -26,7 +26,8 @@ Suggests:
     bookdown,
     lubridate,
     purrr,
-    ggplot2
+    ggplot2,
+    R.rsp
 Biarch: true
 Config/testthat/edition: 3
 Imports: 
@@ -50,4 +51,4 @@ SystemRequirements: GNU make
 Depends: 
     R (>= 3.4.0)
 License: Apache License (>= 2)
-VignetteBuilder: knitr
+VignetteBuilder: R.rsp

R/ancova.R

@@ -159,7 +159,7 @@ ancova <- function(data, vars, visits = NULL, weights = c("proportional", "equal
 #' @param group Character, the name of the group variable in `data`.
 #' @param covariates Character vector containing the name of any additional covariates
 #' to be included in the model as well as any interaction terms.
-#' @param weights Character, specifies wether to use "proportional" or "equal" weighting for each
+#' @param weights Character, specifies whether to use "proportional" or "equal" weighting for each
 #' categorical covariate combination when calculating the lsmeans.
 #'
 #' @details

R/dataclasses.R

@@ -199,7 +199,7 @@ print.imputation_df <- function(x, ...) {
 #' which contains a matrix of [imputation_single()] objects grouped by a single `id`. The matrix
 #' is split so that it has D columns (i.e. for non-bmlmi methods this will always be 1)
 #'
-#' The `id` attribute is deterimined by extracting the `id` attribute from the contributing
+#' The `id` attribute is determined by extracting the `id` attribute from the contributing
 #' [imputation_single()] objects. An error is throw if multiple `id` are detected
 imputation_list_single <- function(imputations, D = 1) {
 

R/delta.R

@@ -231,7 +231,7 @@ get_delta_template <- function(imputations) {
 }
 
 
-#' Calculate delta from a lagged Sscale coefficient
+#' Calculate delta from a lagged scale coefficient
 #'
 #' @description
 #' Calculates a delta value based upon a baseline delta value and a

R/draws.R

@@ -133,7 +133,7 @@
 #' - `group`: name of the column in `data` which contains the group variable.
 #' - `outcome`: name of the column in `data` which contains the outcome variable.
 #' - `covariates`: vector of characters which contains the covariates to be included
-#'   in the model (including interactions which are specified as "covariateName1*covariateName2").
+#'   in the model (including interactions which are specified as `"covariateName1*covariateName2"``).
 #'   If no covariates are provided the default model specification of `outcome ~ 1 + visit + group` will be used.
 #'   Please note that the `group*visit` interaction
 #'   is **not** included in the model by default.
@@ -283,7 +283,7 @@ draws.bmlmi <- function(data, data_ice = NULL, vars, method, ncores = 1, quiet =
 #'
 #' This function takes a `Stack` object which contains multiple lists of patient ids. The function
 #' takes this Stack and pulls a set ids and then constructs a dataset just consisting of these
-#' patients (i.e. potentially a boostrap or a jackknife sample).
+#' patients (i.e. potentially a bootstrap or a jackknife sample).
 #'
 #' The function then fits a MMRM model to this dataset to create a sample object. The function
 #' repeats this process until `n_target_samples` have been reached. If more than `failure_limit`

R/impute.R

@@ -221,7 +221,7 @@ impute_internal <- function(draws, references = NULL, update_strategy, strategie
 #' that are required for that dataset. The total number of ID's must by equal to the
 #' total number of rows within all of `imputes$imputations`
 #'
-#' To accomdate for `method_bmlmi()` the [impute_data_individual()] function returns
+#' To accommodate for `method_bmlmi()` the [impute_data_individual()] function returns
 #' a list of [imputation_list_single()] objects with 1 object per each subject.
 #'
 #' [imputation_list_single()] stores the subjects imputations as a matrix where the columns
@@ -280,7 +280,7 @@ impute_internal <- function(draws, references = NULL, update_strategy, strategie
 #' )
 #' ```
 #'
-#' Note that the different repititions (i.e. the value set for D) are grouped together
+#' Note that the different repetitions (i.e. the value set for D) are grouped together
 #' sequentially.
 #'
 convert_to_imputation_list_df <- function(imputes, sample_ids) {

R/longData.R

@@ -491,7 +491,7 @@ longDataConstructor <- R6::R6Class(
 
         #' @description
         #' Constructor function.
-        #' @param data longditudinal dataset.
+        #' @param data longitudinal dataset.
         #' @param vars an `ivars` object created by [set_vars()].
         initialize = function(data, vars) {
             data_raw <- as_dataframe(data)

R/lsmeans.R

@@ -31,7 +31,7 @@
 #' @param ... Fixes specific variables to specific values i.e.
 #' `trt = 1` or `age = 50`. The name of the argument must be the name
 #' of the variable within the dataset.
-#' @param .weights Character, specifies wether to use "proportional" or "equal" weighting for each
+#' @param .weights Character, specifies whether to use "proportional" or "equal" weighting for each
 #' categorical covariate combination when calculating the lsmeans.
 #'
 #' @references \url{https://CRAN.R-project.org/package=emmeans}

R/mcmc.R

@@ -126,8 +126,8 @@ fit_mcmc <- function(
     }
 
     ignorable_warnings <- c(
-        "Bulk Effective Samples Size (ESS) is too low, indicating posterior means and medians may be unreliable.\nRunning the chains for more iterations may help. See\nhttp://mc-stan.org/misc/warnings.html#bulk-ess",
-        "Tail Effective Samples Size (ESS) is too low, indicating posterior variances and tail quantiles may be unreliable.\nRunning the chains for more iterations may help. See\nhttp://mc-stan.org/misc/warnings.html#tail-ess"
+        "Bulk Effective Samples Size (ESS) is too low, indicating posterior means and medians may be unreliable.\nRunning the chains for more iterations may help. See\nhttps://mc-stan.org/misc/warnings.html#bulk-ess",
+        "Tail Effective Samples Size (ESS) is too low, indicating posterior variances and tail quantiles may be unreliable.\nRunning the chains for more iterations may help. See\nhttps://mc-stan.org/misc/warnings.html#tail-ess"
     )
 
     # handle warning: display only warnings if

R/mmrm.R

@@ -175,7 +175,7 @@ extract_params <- function(fit) {
 #' @param group a character / factor vector. Indicates which treatment group the patient belongs to.
 #' @param cov_struct a character value. Specifies which covariance structure to use. Must be one of
 #' `"us"`, `"toep"`, `"cs"` or  `"ar1"`
-#' @param REML logical. Specifies whether restricted maximium likelihood should be used
+#' @param REML logical. Specifies whether restricted maximum likelihood should be used
 #' @param same_cov logical. Used to specify if a shared or individual covariance matrix should be used
 #' per `group`
 #' @param initial_values a list with names `beta` and `theta`. Specifies the initial values to start

R/parallel.R

@@ -5,7 +5,7 @@
 #'
 #' This function spawns a PSOCK cluster and exports all of the
 #' rbmi namespace into the the sub processes as well as loading
-#' assertthat and glmmTMB
+#' `assertthat` and `glmmTMB`
 get_cluster <- function(ncores = 1) {
     if (ncores == 1) {
         return(NULL)

R/strategies.R

@@ -20,7 +20,7 @@
 #' @references
 #' Carpenter, James R., James H. Roger, and Michael G. Kenward. "Analysis of longitudinal
 #' trials with protocol deviation: a framework for relevant, accessible assumptions, and
-#' inference via multiple imputation." Journal of biopharmaceutical statistics 23.6 (2013):
+#' inference via multiple imputation." Journal of Biopharmaceutical statistics 23.6 (2013):
 #' 1352-1371.
 compute_sigma <- function(sigma_group, sigma_ref, index_mar) {
 

R/utilities.R

@@ -506,7 +506,7 @@ is_num_char_fact <- function(x) {
 #' @param x a data.frame like object
 #'
 #' Utility function to convert a "data.frame-like" object to an actual `data.frame`
-#' to avoid issues with inconsitencies on methods (such as  `[`() and dplyr's grouped dataframes)
+#' to avoid issues with inconsistency on methods (such as  `[`() and dplyr's grouped dataframes)
 as_dataframe <- function(x) {
     x2 <- as.data.frame(x)
     row.names(x2) <- NULL

cran-comments.md

@@ -1,12 +1,3 @@
-## Test environments
-
-The package was tested in the following environments (in GitHub actions):
-
-- Ubuntu 20.04, R release
-- Windows latest, R release
-- Mac OS latest, R release
-- Ubuntu 20.04, R devel
-
 ## R CMD check results
 
 There were no ERRORs or WARNINGs.
@@ -26,7 +17,18 @@ There were 3 NOTEs:
 ❯ checking for GNU extensions in Makefiles ... NOTE
   GNU make is a SystemRequirements.
 
-Both of the above notes are a consequence of using rstan in the package following the usage steps as described by the stan developers [here](https://cran.r-project.org/web/packages/rstantools/vignettes/minimal-rstan-package.html). Our understanding from the developers is that they are acceptable to ignore. 
+Both of the above notes are a consequence of using rstan in the package following the usage steps as described by the stan developers [here](https://cran.r-project.org/web/packages/rstantools/vignettes/minimal-rstan-package.html). Our understanding from the [developers](https://discourse.mc-stan.org/t/using-rstan-in-an-r-package-generates-r-cmd-check-notes/26628) is that they are acceptable to ignore. 
+
+
+## Test environments
+
+The package was tested in the following environments (in GitHub actions):
+
+- Ubuntu 20.04, R release
+- Windows latest, R release
+- Mac OS latest, R release
+- Ubuntu 20.04, R devel
+
 
 ## Downstream dependencies
 

misc/docker/install_packages.R

@@ -17,7 +17,8 @@ pkgs <- c(
     "roxygen2",
     "tinytex",
     "bookdown",
-    "RhpcBLASctl"
+    "RhpcBLASctl",
+    "R.rsp"
 )
 
 options(warn = 2)