Updated documentation

elliecurnow · Aug 5, 2024 · bd40789 · bd40789
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diff --git a/R/checkcra.R b/R/checkcra.R
@@ -27,7 +27,8 @@
 #' @export
 #'
 #' @examples
-#' # Example DAG for which complete records analysis is not valid
+#' # Example DAG for which complete records analysis is not valid, but could be
+#'   ## valid for a different set of covariates
 #' checkCRA(y="bmi7", covs="matage", r_cra="r",
 #'   mdag="matage -> bmi7 mated -> matage mated -> bmi7 sep_unmeas ->
 #'   mated sep_unmeas -> r")
@@ -37,17 +38,17 @@
 #'   mdag="matage -> bmi7 mated -> matage mated -> bmi7 sep_unmeas ->
 #'   mated sep_unmeas -> r")
 #'
-#' # Example DAG for which complete records analysis is not valid
-#' checkCRA(y="bmi7", covs="matage mated", r_cra="r",
-#'   mdag="matage -> bmi7 mated -> matage mated -> bmi7 sep_unmeas ->
-#'   mated sep_unmeas -> r bmi7 -> r")
-#'
 #' # Example DAG for which complete records is not valid, but could be valid
 #'   ## for a different estimand
 #' checkCRA(y="bmi7", covs="matage mated", r_cra="r",
 #'   mdag="matage -> bmi7 mated -> matage mated -> bmi7 sep_unmeas ->
 #'   mated sep_unmeas -> r matage -> bmi3 mated -> bmi3 bmi3 -> bmi7
 #'   bmi3 -> r")
+#'
+#' # Example DAG for which complete records analysis is not valid
+#' checkCRA(y="bmi7", covs="matage mated", r_cra="r",
+#'   mdag="matage -> bmi7 mated -> matage mated -> bmi7 sep_unmeas ->
+#'   mated sep_unmeas -> r bmi7 -> r")
 checkCRA <- function(y, covs, r_cra, mdag) {
   mdagspec <- paste('dag {',mdag,'}')
   covsvec <- unlist(strsplit(covs," "))

diff --git a/R/proposeMI.R b/R/proposeMI.R
@@ -34,8 +34,8 @@
 #' # Display the proposed 'mice' options
 #'   ## When specifying a single imputation model
 #' proposeMI(mimodobj=mimod_bmi7, data=bmi)
-#'   ## When specifying more than one imputation model
-#' proposeMI(mimodobj=list(mimod_bmi7,mimod_pregsize), data=bmi)
+#'   ## When specifying more than one imputation model (suppressing the plot)
+#' proposeMI(mimodobj=list(mimod_bmi7,mimod_pregsize), data=bmi, plot = FALSE)
 proposeMI <- function(mimodobj, data, message = TRUE, plot = TRUE, plotprompt = TRUE) {
 
   m_min <- ceiling((1-mean(ifelse(apply(data,1,anyNA)==F,1,0)))*100)