Strata as factor in svydesign

DESCRIPTION

@@ -1,8 +1,8 @@
 Package: SUMMER
 Type: Package
 Title: Small-Area-Estimation Unit/Area Models and Methods for Estimation in R
-Version: 1.4.0
-Date: 2024-02-29
+Version: 1.4.1
+Date: 2024-04-07
 Authors@R: c(
     person(given = "Zehang R", family = "Li", email= "[email protected]", role = c("cre","aut")),
     person(given = "Bryan D", family = "Martin", email= "[email protected]", role = "aut"), 

R/countrySummary.R

@@ -88,6 +88,8 @@ getDirect <- function(births, years, regionVar = "region", timeVar = "time", clu
 
     if (is.null(births$strata)) {
         stop("Strata not defined.")
+    }else{
+        births$strata <- factor(births$strata)
     }
     if (is.null(clusterVar)){
         stop("Cluster not defined")

R/fitspace.R

@@ -87,7 +87,8 @@
 #' head(fit0.draws$draws.est[, 1:10]) 
 #' 
 #' # Example with region-level covariates
-#'  Xmat <- aggregate(age~region, data = DemoData2, FUN = mean)
+#'  Xmat <- aggregate(age~region, data = DemoData2, 
+#' 						FUN = function(x) mean(x))
 #'  fit1 <- smoothSurvey(data=DemoData2,  
 #'   Amat=DemoMap2$Amat, responseType="binary", 
 #'   X = Xmat,
@@ -372,7 +373,7 @@ smoothSurvey <- function(data, geo = NULL, Amat = NULL, region.list = NULL, X =
             stop("Exist regions in the data frame but not in Amat.")
         }
         data$region0 <- factor(data$region0, levels = colnames(Amat))
-        data$strata0 <- data[, strataVar.within]
+        data$strata0 <- factor(data[, strataVar.within])
         if(!is.null(clusterVar)) data$cluster0 <- data[, clusterVar]
 
         # check column names of covariates

R/summary.R

@@ -84,8 +84,8 @@ summary.SUMMERmodel <- function(object,...){
 	hyperpar <- summary(object$fit)$hyperpar
 	print(hyperpar)
 
-	neffp <- summary(object$fit)$neffp
-	print(neffp)
+	# neffp <- summary(object$fit)$neffp
+	# print(neffp)
 	mlik <- summary(object$fit)$mlik
 	print(mlik)
 }
@@ -311,8 +311,8 @@ summary.SUMMERmodel.svy <- function(object,...){
 	hyperpar <- summary(object$fit)$hyperpar
 	print(hyperpar)
 
-	neffp <- summary(object$fit)$neffp
-	print(neffp)
+	# neffp <- summary(object$fit)$neffp
+	# print(neffp)
 	mlik <- summary(object$fit)$mlik
 	print(mlik)
 }