Update support_blocks with master

Merge branch 'master' into support_blocks

# Conflicts:
#	DESCRIPTION
#	NEWS.md
#	R/ampute.R
#	R/method.R
#	R/mice.R
#	R/mice.impute.rf.R
#	man/ampute.Rd
#	man/mice.Rd
#	man/mice.impute.rf.Rd
#	tests/testthat/test-parlmice.R

.github/workflows/pkgdown.yaml

@@ -41,7 +41,7 @@ jobs:
 
       - name: Deploy to GitHub pages 🚀
         if: github.event_name != 'pull_request'
-        uses: JamesIves/[email protected].0
+        uses: JamesIves/[email protected].9
         with:
           clean: false
           branch: gh-pages

DESCRIPTION

@@ -1,8 +1,8 @@
 Package: mice
 Type: Package
-Version: 3.999.1
+Version: 3.16.16
 Title: Multivariate Imputation by Chained Equations
-Date: 2024-04-17
+Date: 2024-10-16
 Authors@R: c(person("Stef", "van Buuren", role = c("aut","cre"),
     email = "[email protected]"),
     person("Karin", "Groothuis-Oudshoorn", role = "aut",
@@ -40,7 +40,9 @@ Authors@R: c(person("Stef", "van Buuren", role = c("aut","cre"),
     person("Caspar", "van Lissa", role = "ctb", 
     email = "[email protected]"),
     person("Hanne", "Oberman", role = "ctb",
-    email = "[email protected]"))
+    email = "[email protected]"),
+    person("Stephen", "Wade", role = "ctb",
+    email = "[email protected]"))
 Maintainer: Stef van Buuren <[email protected]>
 Depends:
     R (>= 2.10.0)
@@ -67,6 +69,7 @@ Suggests:
     furrr,
     haven,
     knitr,
+    literanger,
     lme4,
     MASS,
     miceadds,
@@ -99,6 +102,4 @@ URL: https://github.com/amices/mice,
 BugReports: https://github.com/amices/mice/issues
 LinkingTo: cpp11, Rcpp
 License: GPL (>= 2)
-Roxygen: list(markdown = TRUE)
-RoxygenNote: 7.3.1
-VignetteBuilder: knitr
+RoxygenNote: 7.3.2

NEWS.md

@@ -43,6 +43,30 @@
 ## -----------------------------------------------------------
 
 
+# mice 3.16.16
+
+* Prevent `as.mids()` from filling the `imp` object for complete variables
+
+# mice 3.16.15
+
+* Initialize single-variables blocks in `make.method()` in a more efficient way (resolves #672)
+
+# mice 3.16.14
+
+* Fixes a bug during initialization of factor values
+
+# mice 3.16.13
+
+* Adds support for the `literanger` package for `rf` imputation that is about twice as fast as `ranger` (#648). Thanks @stephematician for the contribution.
+
+# mice 3.16.12
+
+* Fixes an installation problem when `Rprofile` prints to `stdout` on Fedora, R version 4.1.3 (#646, #647). Thanks @brookslogan for the fix.
+
+# mice 3.16.11
+
+* Repairs lost braces in the documentation
+
 # mice 3.16.10
 
 * Adds support for non-syntactic variables names with backticks (#631)

R/ampute.R

@@ -84,8 +84,9 @@
 #'
 #' For an example and more explanation about how the arguments interact with each other,
 #' we refer to the vignette
-#' [Generate missing values with ampute](https://rianneschouten.github.io/mice_ampute/vignette/ampute.html)
-#' The amputation methodology is published in \doi{10.1080/00949655.2018.1491577}.
+#' \href{https://rianneschouten.github.io/mice_ampute/vignette/ampute.html}{Generate missing values with ampute}
+#' The amputation methodology is published in
+#' \doi{10.1080/00949655.2018.1491577}
 #'
 #' @param data A complete data matrix or data frame. Values should be numeric.
 #' Categorical variables should have been transformed to dummies.
@@ -160,21 +161,23 @@
 #' incomplete data sets.* pp. 110-113. Dissertation. Rotterdam: Erasmus University.
 #'
 #' Schouten, R.M., Lugtig, P and Vink, G. (2018)
-#' {Generating missing values for simulation purposes: A multivariate amputation procedure.}.
-#' *Journal of Statistical Computation and Simulation*, 88(15): 1909-1930.
+#' Generating missing values for simulation purposes: A multivariate
+#' amputation procedure.
+#' \emph{Journal of Statistical Computation and Simulation}, 88(15): 1909-1930.
 #' \doi{10.1080/00949655.2018.1491577}
 #'
-#' Schouten, R.M. and Vink, G. (2018){The Dance of the Mechanisms: How Observed Information Influences the Validity of Missingness Assumptions}.
-#' *Sociological Methods and Research*, 50(3): 1243-1258.
+#' Schouten, R.M. and Vink, G. (2018) The Dance of the Mechanisms: How Observed
+#' Information Influences the Validity of Missingness Assumptions.
+#' \emph{Sociological Methods and Research}, 50(3): 1243-1258.
 #' \doi{10.1177/0049124118799376}
 #'
 #' Van Buuren, S., Brand, J.P.L., Groothuis-Oudshoorn, C.G.M., Rubin, D.B. (2006)
-#' {Fully conditional specification in multivariate imputation.}
-#' *Journal of Statistical Computation and Simulation*, 76(12): 1049-1064.
+#' Fully conditional specification in multivariate imputation.
+#' \emph{Journal of Statistical Computation and Simulation}, 76(12): 1049-1064.
 #' \doi{10.1080/10629360600810434}
 #'
-#' Van Buuren, S. (2018)
-#' [*Flexible Imputation of Missing Data. Second Edition.*](https://stefvanbuuren.name/fimd)
+#' Van Buuren, S. (2018).
+#' \emph{Flexible Imputation of Missing Data. Second Edition.}
 #' Chapman & Hall/CRC. Boca Raton, FL.
 #'
 #' Vink, G. (2016) Towards a standardized evaluation of multiple imputation routines.

R/as.R

@@ -124,7 +124,7 @@ as.mids <- function(long, where = NULL, .imp = ".imp", .id = ".id") {
   names <- names(ini$imp)
   for (i in seq_along(names)) {
     varname <- names[i]
-    if (!is.null(ini$imp[[varname]])) {
+    if (nrow(ini$imp[[varname]])) {
       for (j in seq_len(m)) {
         idx <- imps == j & where[, varname]
         ini$imp[[varname]][j] <- long[idx, varname]

R/initialize.imp.R

@@ -24,7 +24,7 @@ initialize.imp <- function(data, m, ignore, where, blocks, visitSequence,
             imp[[j]][, i] <- data.init[wy, j]
           } else {
             if (is.factor(y)) {
-              imp[[j]][, i] <- sample(levels(y), nrow(data))
+              imp[[j]][, i] <- sample(levels(y), nrow(data), replace = TRUE)
             } else {
               imp[[j]][, i] <- rnorm(nrow(data))
             }

R/mice-package.R

@@ -56,8 +56,9 @@
 #'
 #' @section Methodology:
 #'
-#' The \pkg{mice} software was published in the {Journal of Statistical Software} (Van Buuren and Groothuis-Oudshoorn, 2011). \doi{10.18637/jss.v045.i03}
-#' The first application of the method
+#' The \pkg{mice} software was published in the
+#' \emph{Journal of Statistical Software} (Van Buuren and Groothuis-Oudshoorn, 2011).
+#' \doi{10.18637/jss.v045.i03}. The first application of the method
 #' concerned missing blood pressure data (Van Buuren et. al., 1999).
 #' The term *Fully Conditional Specification* was introduced in 2006 to describe a general class of methods that specify imputations model for multivariate data as a set of conditional distributions (Van Buuren et. al., 2006). Further details on mixes of variables and applications can be found in the book
 #' [*Flexible Imputation of Missing Data. Second Edition.*](https://stefvanbuuren.name/fimd/)

R/mice.R

@@ -342,7 +342,7 @@
 #' \doi{10.18637/jss.v045.i03}
 #'
 #' Van Buuren, S. (2018).
-#' [*Flexible Imputation of Missing Data. Second Edition.*](https://stefvanbuuren.name/fimd/sec-FCS.html#sec:MICE)
+#' \emph{Flexible Imputation of Missing Data. Second Edition.}
 #' Chapman & Hall/CRC. Boca Raton, FL.
 #'
 #' Van Buuren, S., Brand, J.P.L., Groothuis-Oudshoorn C.G.M., Rubin, D.B. (2006)
@@ -354,8 +354,8 @@
 #' Research*, **16**, 3, 219--242.
 #'
 #' Van Buuren, S., Boshuizen, H.C., Knook, D.L. (1999) Multiple imputation of
-#' missing blood pressure covariates in survival analysis.  *Statistics in
-#' Medicine*, **18**, 681--694.
+#' missing blood pressure covariates in survival analysis.
+#' \emph{Statistics in Medicine}, \bold{18}, 681--694.
 #'
 #' Brand, J.P.L. (1999) *Development, implementation and evaluation of
 #' multiple imputation strategies for the statistical analysis of incomplete

R/mice.impute.pmm.R

@@ -61,7 +61,9 @@
 #' \item{Calculate \eqn{\dot\beta = \hat\beta + \dot\sigma\dot z_1 V^{1/2}}.}
 #' \item{Calculate \eqn{\dot\eta(i,j)=|X_{{obs},[i]|}\hat\beta-X_{{mis},[j]}\dot\beta}
 #' with \eqn{i=1,\dots,n_1} and \eqn{j=1,\dots,n_0}.}
-#' \item{Construct \eqn{n_0} sets \eqn{Z_j}, each containing \eqn{d} candidate donors, from Y_{obs} such that \eqn{\sum_d\dot\eta(i,j)} is minimum for all \eqn{j=1,\dots,n_0}. Break ties randomly.}
+#' \item{Construct \eqn{n_0} sets \eqn{Z_j}, each containing \eqn{d}
+#' candidate donors, from \eqn{y_{obs}} such that \eqn{\sum_d\dot\eta(i,j)} is
+#' minimum for all \eqn{j=1,\dots,n_0}. Break ties randomly.}
 #' \item{Draw one donor \eqn{i_j} from \eqn{Z_j} randomly for \eqn{j=1,\dots,n_0}.}
 #' \item{Calculate imputations \eqn{\dot y_j = y_{i_j}} for \eqn{j=1,\dots,n_0}.}
 #' }

R/mice.impute.rf.R

@@ -6,14 +6,17 @@
 #' @inheritParams mice.impute.pmm
 #' @param ntree The number of trees to grow. The default is 10.
 #' @param rfPackage A single string specifying the backend for estimating the
-#' random forest. The default backend is the `ranger` package. The only
-#' alternative currently implemented is the `randomForest` package, which
-#' used to be the default in mice 3.13.10 and earlier.
+#' random forest. The default backend is the \code{ranger} package. An
+#' alternative is \code{literanger} which predicts faster but does not support
+#' all forest types and split rules from \code{ranger}. Also implemented as
+#' an alternative is the \code{randomForest} package, which used to be the
+#' default in mice 3.13.10 and earlier.
 #' @param \dots Other named arguments passed down to
-#' `mice:::install.on.demand()`, `randomForest::randomForest()`,
-#' `randomForest:::randomForest.default()`, and `ranger::ranger()`.
-#' @return Vector with imputed data, same type as `y`, and of length
-#' `sum(wy)`
+#' \code{mice:::install.on.demand()}, \code{randomForest::randomForest()},
+#' \code{randomForest:::randomForest.default()}, \code{ranger::ranger()}, and
+#' \code{literanger::train()}.
+#' @return Vector with imputed data, same type as \code{y}, and of length
+#' \code{sum(wy)}
 #' @details
 #' Imputation of `y` by random forests. The method
 #' calls `randomForrest()` which implements Breiman's random forest
@@ -43,9 +46,10 @@
 #' Van Buuren, S. (2018).
 #' [*Flexible Imputation of Missing Data. Second Edition.*](https://stefvanbuuren.name/fimd/sec-cart.html)
 #' Chapman & Hall/CRC. Boca Raton, FL.
-#' @seealso [mice()], [mice.impute.cart()],
-#' [randomForest::randomForest()]
-#' [ranger::ranger()]
+#' @seealso \code{\link{mice}}, \code{\link{mice.impute.cart}},
+#' \code{\link[randomForest]{randomForest}},
+#' \code{\link[ranger]{ranger}},
+#' \code{\link[literanger]{train}}
 #' @family univariate imputation functions
 #' @keywords datagen
 #' @examples
@@ -55,7 +59,8 @@
 #' }
 #' @export
 mice.impute.rf <- function(y, ry, x, wy = NULL, ntree = 10,
-                           rfPackage = c("ranger", "randomForest"), ...) {
+                           rfPackage = c("ranger", "randomForest", "literanger"),
+                           ...) {
   rfPackage <- match.arg(rfPackage)
 
   if (is.null(wy)) wy <- !ry
@@ -69,11 +74,14 @@ mice.impute.rf <- function(y, ry, x, wy = NULL, ntree = 10,
   # Find eligible donors
   f <- switch(rfPackage,
     randomForest = .randomForest.donors,
-    ranger = .ranger.donors
+    ranger = .ranger.donors,
+    literanger = .literanger.donor
   )
 
   forest <- f(xobs, xmis, yobs, ntree, ...)
 
+  # Short-circuit when using literanger interface
+  if (rfPackage == "literanger") return(forest)
   # Sample from donors
   if (nmis == 1) forest <- array(forest, dim = c(1, ntree))
   apply(forest, MARGIN = 1, FUN = function(s) sample(unlist(s), 1))
@@ -124,3 +132,17 @@ mice.impute.rf <- function(y, ry, x, wy = NULL, ntree = 10,
 
   sapply(seq_len(ntree), FUN = select_donors)
 }
+
+# Find eligible donors using the literanger package
+.literanger.donor <- function(xobs, xmis, yobs, ntree, ...) {
+  install.on.demand("literanger", ...)
+
+  lr_formals <- names(formals(literanger::train))
+  dots <- list(...)
+  dots <- dots[intersect(names(dots), setdiff(lr_formals, c('x', 'y')))]
+
+  fit <- do.call(
+    literanger::train, c(list(x = xobs, y = yobs, n_tree = ntree), dots)
+  )
+  predict(object = fit, newdata = xmis, prediction_type = "inbag")$values
+}

README.Rmd

@@ -23,7 +23,7 @@ set.seed(1)
 [![CRAN_Status_Badge](https://www.r-pkg.org/badges/version/mice)](https://cran.r-project.org/package=mice)
 [![](https://cranlogs.r-pkg.org/badges/mice)](https://cran.r-project.org/package=mice)
 [![R-CMD-check](https://github.com/amices/mice/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/amices/mice/actions/workflows/R-CMD-check.yaml)
-[![](https://img.shields.io/badge/github%20version-3.16.10-orange.svg)](https://amices.org/mice/)
+[![](https://img.shields.io/badge/github%20version-3.16.16-orange.svg)](https://amices.org/mice/)
 <!-- badges: end -->
 
 ## [Multivariate Imputation by Chained Equations](https://amices.org/mice/)

README.md

@@ -7,7 +7,7 @@
 [![CRAN_Status_Badge](https://www.r-pkg.org/badges/version/mice)](https://cran.r-project.org/package=mice)
 [![](https://cranlogs.r-pkg.org/badges/mice)](https://cran.r-project.org/package=mice)
 [![R-CMD-check](https://github.com/amices/mice/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/amices/mice/actions/workflows/R-CMD-check.yaml)
-[![](https://img.shields.io/badge/github%20version-3.16.10-orange.svg)](https://amices.org/mice/)
+[![](https://img.shields.io/badge/github%20version-3.16.16-orange.svg)](https://amices.org/mice/)
 <!-- badges: end -->
 
 ## [Multivariate Imputation by Chained Equations](https://amices.org/mice/)