Fix a bug of MI extraction

R/data.R

@@ -25,3 +25,17 @@
 #' }
 #' @source long-to-wise tranformation of schizo data, i.e. schizob = data.table::dcast(schizo, id + tx ~ week, value.var = "imps79b")
 "schizob"
+
+
+#' wide format of continuous response of antidepressant data.
+#'
+#' A data set containing the treatment and continuous responses measured at baseline and 4 post-baseline visits
+#'
+#' @format A data frame with 172 rows and 6 variables:
+#' \describe{
+#'   \item{PID}{Patient ID}
+#'   \item{tx}{Treatment, 1 for treated and 0 for placebo}
+#'   \item{y0}{HADM-17 measurement at the baseline}
+#'   \item{y1, y2, y4, y6}{Change score of HADM-17 measurement at the post-baseline week 1, 2, 4, and 6.}
+#' }
+#' @source https://www.lshtm.ac.uk/research/centres-projects-groups/missing-data#dia-missing-data

R/glm_MI_CR.R

@@ -83,7 +83,7 @@ glm_MI_CR <- function(object, treatment, start=NULL, end=NULL, thin=NULL,
           }
 
     coefs <- coef_list[[vimp[j]]]
-    if (nrow(vdv)>0) {
+    if (length(refs) > 0) {
       coefs <- merge(coefs, vdv, by="varname", all.x=TRUE)
       coefs$var[is.na(coefs$var)] = "inter"
     } else {

R/glm_MI_J2R.R

@@ -90,7 +90,7 @@ glm_MI_J2R <- function(object, treatment, start=NULL, end=NULL, thin=NULL,
                   }
 
     coefs <- coef_list[[vimp[j]]]
-    if (nrow(vdv)>0) {
+    if (length(refs) > 0) {
       coefs <- merge(coefs, vdv, by="varname", all.x=TRUE)
       coefs$var[is.na(coefs$var)] = "inter"
     } else {

R/glm_MI_delta.R

@@ -85,7 +85,7 @@ glm_MI_delta <- function(object, treatment, delta=0, start=NULL, end=NULL, thin=
           }
 
     coefs <- coef_list[[vimp[j]]]
-    if (nrow(vdv)>0) {
+    if (length(refs) > 0) {
       coefs <- merge(coefs, vdv, by="varname", all.x=TRUE)
       coefs$var[is.na(coefs$var)] = "inter"
     } else {

R/list.models.R

@@ -36,15 +36,19 @@ list.models <- function (object, details = FALSE, print = TRUE) {
     refs = Mlist$refs
 
     ## dummy vars -->> original varname
-    vdvlist = lapply(names(refs), function(dv) data.frame(var=dv, varname=attr(refs[[dv]],"dummies")) )
-    vdv = do.call(rbind.data.frame, vdvlist)
-
+    if (length(refs)>0){
+      vdvlist = lapply(names(refs), function(dv) data.frame(var=dv, varname=attr(refs[[dv]],"dummies")) )
+      vdv = do.call(rbind.data.frame, vdvlist)
+    }
     vimp = rev(names(info_list))
 
     for (j in 1:length(vimp)){
       varname = vimp[j]
       coefs <- coef_list[[vimp[j]]]
-      coefs <- merge(coefs, vdv, by="varname", all.x=TRUE)
+
+      if (length(refs)>0) coefs <- merge(coefs, vdv, by="varname", all.x=TRUE)
+      else coefs$var = coefs$varname
+
       coefs$var[is.na(coefs$var)] = coefs$varname[is.na(coefs$var)]
       coefs = subset(coefs, !grepl("intercept", var,ignore.case = TRUE))
       dtj = data.frame(Order=j, model_formula = paste0(varname," ~ ", paste(unique(coefs$var), collapse = " + ")))