Merge branch 'hotfix-ordered-factor' (0.3.5)

DESCRIPTION

@@ -1,8 +1,8 @@
 Package: tableone
 Type: Package
 Title: Create "Table 1" to describe baseline characteristics
-Version: 0.3.4
-Date: 2014-03-04
+Version: 0.3.5
+Date: 2014-03-07
 Author: Kazuki Yoshida, Justin Bohn
 Maintainer: Kazuki Yoshida <[email protected]>
 Description: This package creates "Table 1", i.e., description of baseline

NEWS

@@ -1,3 +1,13 @@
+tableone 0.3.5 (2014-03-07)
+----------------------------------------------------------------
+
+BUG FIXES
+
+* Added more robust class assessment in CreateTableOne and
+  CreateCatTable, which now handles ordered factors correctly.
+  CreateTableOne also drops Surv object for safety.
+
+
 tableone 0.3.4 (2014-03-04)
 ----------------------------------------------------------------
 

R/CreateCatTable.R

@@ -42,7 +42,7 @@
 ##'
 ##' ## If you need to show both levels for some 2-level factors, use cramVars
 ##' print(catTableOverall, cramVars = "hepato")
-##' 
+##'
 ##' ## Use the showAllLevels argument to see all levels for all variables.
 ##' print(catTableOverall, showAllLevels = TRUE)
 ##'
@@ -106,8 +106,13 @@ CreateCatTable <-
 
     ## Convert to a factor if it is not a factor already. (categorical version only)
     ## Not done on factors, to avoid dropping zero levels.
-    datNotFactor <- sapply(dat, class) != "factor"
-    dat[datNotFactor] <- lapply(dat[datNotFactor], factor)
+    ## Probably this cannot handle Surv object??
+    logiNotFactor <- sapply(dat, function(VEC) {
+        ## Return TRUE if classes for a vector does NOT contain class "factor"
+        !any(VEC %in% c("factor"))
+    })
+
+    dat[logiNotFactor] <- lapply(dat[logiNotFactor], factor)
 
     ## Create strata data frame (data frame with only strata variables)
     strata <- ModuleReturnStrata(strata, data)

R/CreateTableOne.R

@@ -118,9 +118,19 @@ CreateTableOne <-
         test <- ModuleReturnFalseIfNoStrata(strata, test)
 
         ## Get the classes of the variables
-        varClasses  <- sapply(data[vars], class)
-        varFactors  <- names(varClasses[varClasses == "factor"  | varClasses == "logical" | varClasses == "character"])
-        varNumerics <- names(varClasses[varClasses == "numeric" | varClasses == "integer"])
+        varClasses  <- lapply(data[vars], class)
+
+        ## Classify as varFactors if any one of these classes are contained
+        varFactors <-sapply(varClasses, function(VEC) {
+            any(VEC %in% c("factor", "ordered", "logical", "character"))
+        })
+        varFactors <- names(varFactors)[varFactors]
+
+        ## Classify as varNumerics if any one of these classes are contained
+        varNumerics <-sapply(varClasses, function(VEC) {
+            any(VEC %in% c("numeric", "integer"))
+        })
+        varNumerics <- names(varNumerics)[varNumerics]
 
         ## Drop variables that do not meet either because it is unsupported
         varDrop <- setdiff(vars, c(varFactors, varNumerics))