for cran

DESCRIPTION

@@ -2,7 +2,7 @@ Package: intsvy
 Version: 2.1
 Type: Package
 Title: International Assessment Data Manager
-Date: 2017-08-10
+Date: 2017-11-08
 Author: Daniel Caro <daniel.caro@education.ox.ac.uk>, Przemyslaw Biecek <przemyslaw.biecek@gmail.com>
 Maintainer: Daniel Caro <daniel.caro@education.ox.ac.uk>
 Description: 
@@ -14,4 +14,4 @@ BugReports: https://github.com/eldafani/intsvy/issues
 Imports: foreign, ggplot2, Hmisc, memisc, plyr, reshape, stats, utils 
 LazyData: yes
 NeedsCompilation: no
-Repository: CRAN
+Repository: CRAN

R/pisa.select.merge.R

@@ -1,6 +1,5 @@
 pisa.select.merge <- 
-  function(folder=getwd(), student.file, parent.file=c(), school.file=c(), countries, student=c(), parent, school, 
-           use.value.labels= FALSE) {
+  function(folder=getwd(), student.file, parent.file=c(), school.file=c(), countries, student=c(), parent, school) {
 
     # Remove leading and trailing whitespaces in var labes  
     if(!missing(student) & !is.null(student)) {
@@ -51,7 +50,7 @@ pisa.select.merge <-
     files.all <- files.all[sapply(files.all, length)>0]
 
     # Participating countries (from student file)
-    pisa.student <- read.spss(files.all[["Student"]], to.data.frame=TRUE, use.value.labels=use.value.labels)
+    pisa.student <- read.spss(files.all[["Student"]], to.data.frame=TRUE, use.value.labels=FALSE)
     country <- names(table(pisa.student[, "CNT"])) 
 
     # If countries missing, all countries selected
@@ -88,7 +87,7 @@ pisa.select.merge <-
       }
 
 
-      pisa.parent <- read.spss(files.all[["Parent"]], to.data.frame=TRUE, use.value.labels=use.value.labels)
+      pisa.parent <- read.spss(files.all[["Parent"]], to.data.frame=TRUE, use.value.labels=FALSE)
       names(pisa.parent) <- toupper(names(pisa.parent))
 
       parent.data <- pisa.parent[pisa.parent[["CNT"]] %in% countries, 
@@ -106,7 +105,7 @@ pisa.select.merge <-
       }
 
 
-      pisa.school <- read.spss(files.all[["School"]], to.data.frame=TRUE, use.value.labels=use.value.labels)
+      pisa.school <- read.spss(files.all[["School"]], to.data.frame=TRUE, use.value.labels=FALSE)
       names(pisa.school) <- toupper(names(pisa.school))
 
 

inst/CITATION

@@ -0,0 +1,18 @@
+bibentry(bibtype = "Article",
+  title        = "{intsvy}: An {R} Package for Analyzing International Large-Scale Assessment Data",
+  author       = c(person(given = c("Daniel", "H."),
+                          family = "Caro",
+                          email = "daniel.caro@education.ox.ac.uk"),
+                   person(given = "Przemys\\l{}aw",
+                          family = "Biecek",
+                          email = "Przemyslaw.Biecek@gmail.com")),
+  journal      = "Journal of Statistical Software",
+  year         = "2017",
+  volume       = "81",
+  number       = "7",
+  pages        = "1--44",
+  doi          = "10.18637/jss.v081.i07",
+
+  header       = "To cite intsvy in publications use:",
+)
+

man/intsvy-package.Rd

@@ -9,12 +9,11 @@
 Package: \tab intsvy\cr
 Type: \tab Package\cr
 Version: \tab 2.1\cr
-Date: \tab 2017-08-10\cr
+Date: \tab 2017-11-08\cr
 License: \tab GPL-2\cr
 }
 intsvy allows useRs to work with international assessment data (e.g., TIMSS, PIRLS, PISA, ICILS, and PIAAC). The data is publicly available @ rms.iea-dpc.org and www.oecd.org/pisa in SPSS format. Data and merge functions print variable labels and the name of participating countries in international assessments as well as import data directly into R for the variables in student, parent, school, and teacher instruments and countries selected by the useR. Analysis functions, including mean statistics, standard deviations, regression estimates, correlation coefficients, and frequency tables, calculate point estimates and standard errors that take into account the complex sample design (i.e., replicate weights) and rotated test forms (i.e., plausible achievement values). 
 }
 
 \author{Daniel Caro <daniel.caro@education.ox.ac.uk>, Przemyslaw Biecek <przemyslaw.biecek@gmail.com>}
-\references{PISA, PIAAC, PIRLS, and TIMSS Technical Reports}
-
+\references{PISA, PIAAC, PIRLS, and TIMSS Technical Reports}

man/pirls.select.merge.Rd

@@ -9,7 +9,7 @@ are selected by default.
 }
 \usage{
 pirls.select.merge(folder = getwd(), countries, student = c(), 
-    home, school, teacher, use.labels=FALSE)
+    home, school, teacher)
 }
 \arguments{
   \item{folder}{
@@ -31,9 +31,6 @@ The data labels for the selected school variables.
 }
   \item{teacher}{
 The data labels for the selected teacher data.
-}
-  \item{use.labels}{
-logical: convert variables with value labels into R factors with those levels? 
 }
 }
 

man/pisa.select.merge.Rd

@@ -8,7 +8,7 @@ pisa.select.merge selects and merges data from PISA. Achievement and weight vari
 }
 \usage{
 pisa.select.merge(folder=getwd(), student.file, parent.file=c(), school.file=c(), 
-countries, student=c(), parent, school, use.value.labels=FALSE)
+countries, student=c(), parent, school)
 }
 \arguments{
   \item{folder}{

man/timssg4.select.merge.Rd

@@ -8,8 +8,7 @@ timssg4.select.merge selects and merges data from TIMSS G4. Achievement and weig
 (all of them) are selected by default.
 }
 \usage{
-timssg4.select.merge(folder = getwd(), countries, student = c(), home, school, teacher, 
-use.labels=FALSE)
+timssg4.select.merge(folder = getwd(), countries, student = c(), home, school, teacher)
 }
 
 \arguments{