This vignettes shows a minimal working example for creating a
codebook via the eatCodebook package. For illustrative
purposes we use the R built in data set iris.
We import the data set using the eatGADS package, which is
automatically installed when eatCodebook is installed. We
also run the checkFormat() function from the
eatGADS package which adds SPSS format
information to the meta data of the data set.
library(eatCodebook)
dat <- eatGADS::import_DF(iris)
#> Sepal.Length has been renamed to Sepal_Length
#> Sepal.Width has been renamed to Sepal_Width
#> Petal.Length has been renamed to Petal_Length
#> Petal.Width has been renamed to Petal_Width
dat <- eatGADS::checkFormat(dat)
#> Format of Variable Sepal_Length will be changed from character(0) to F3.1
#> Format of Variable Sepal_Width will be changed from character(0) to F3.1
#> Format of Variable Petal_Length will be changed from character(0) to F3.1
#> Format of Variable Petal_Width will be changed from character(0) to F3.1
#> Format of Variable Species will be changed from character(0) to F1Descriptive Statistics
One of the key elements of a codebook are descriptive statistics
shortly describing each variable in the data set. What kind of
descriptive statistics is reported for each variable depends on the type
of the variable. The function createInputForDescriptives()
creates a template to provide the information that is needed to
calculate the descriptive statistics for an GADSdat
object.
inputForDescriptives <- createInputForDescriptives(GADSdat = dat)
head(inputForDescriptives)
#> varName varLabel format imp type scale group
#> FALSE.1 Sepal_Length <NA> F3.1 FALSE variable numeric Sepal_Length
#> FALSE.2 Sepal_Width <NA> F3.1 FALSE variable numeric Sepal_Width
#> FALSE.3 Petal_Length <NA> F3.1 FALSE variable numeric Petal_Length
#> FALSE.4 Petal_Width <NA> F3.1 FALSE variable numeric Petal_Width
#> FALSE.5 Species <NA> F1 FALSE variable ordinal SpeciesThe template should be exported to .xlsx, modified and
reimported to R.
writeExcel(inputForDescriptives, "inputForDescriptives.xlsx")
inputForDescriptives_edited <- getInputForDescriptives("inputForDescriptives.xlsx")This input is then used to calculate descriptive statistics via
calculateDescriptives().
# calculate descriptives
descStatistics <- calculateDescriptives(GADSdat = dat,
inputForDescriptives = inputForDescriptives_edited)
descStatistics[[3]]
#> N.valid mean.valid sd.valid min.valid max.valid
#> "150" "5.84" "0.83" "4.3" "7.9"
#> sysmis.totalabs
#> "0"Value and Missing Labels
Another important part of a codebook is the documentation of the
value labels of valid and missing values. A respective overview is
created via createMissings().
missings <- createMissings(dat, inputForDescriptives = inputForDescriptives_edited)
head(missings)
#> Var.name Wert missing LabelSH Zeilenumbruch_vor_Wert
#> 5 Species 1 nein setosa nein
#> 6 Species 2 nein versicolor nein
#> 7 Species 3 nein virginica neinIn this case, the resulting object missings has to be
written to xlsx and imported via
getMissings(). Note that all the getXXX
functions perform important cleaning and preparation steps, therefore
the exporting to xlsx is obligatory.
writeExcel(missings, "example_miss.xlsx", row.names = FALSE)
miss_final <- getMissings("example_miss.xlsx")#> Var.name Wert missing LabelSH Zeilenumbruch_vor_Wert
#> 1 Species 1 nein setosa nein
#> 2 Species 2 nein versicolor nein
#> 3 Species 3 nein virginica neinVariable Information
A key element of the eatCodebook package is that various
forms of variable information can be supplied.
varInfo <- createVarInfo(dat, inputForDescriptives = inputForDescriptives_edited)
head(varInfo)
#> Var.Name in.DS.und.SH Unterteilung.im.Skalenhandbuch Layout LabelSH
#> 1 Sepal_Length ja NA - <NA>
#> 2 Sepal_Width ja NA - <NA>
#> 3 Petal_Length ja NA - <NA>
#> 4 Petal_Width ja NA - <NA>
#> 5 Species ja NA - <NA>
#> Anmerkung.Var Gliederung Reihenfolge Titel rekodiert QuelleSH Instruktionen
#> 1 - - NA <NA> nein - -
#> 2 - - NA <NA> nein - -
#> 3 - - NA <NA> nein - -
#> 4 - - NA <NA> nein - -
#> 5 - - NA <NA> nein - -
#> Hintergrundmodell HGM.Reihenfolge HGM.Variable.erstellt.aus intern.extern
#> 1 nein - - -
#> 2 nein - - -
#> 3 nein - - -
#> 4 nein - - -
#> 5 nein - - -
#> Seitenumbruch.im.Inhaltsverzeichnis
#> 1 nein
#> 2 nein
#> 3 nein
#> 4 nein
#> 5 nein
writeExcel(varInfo, "example_varInfo.xlsx", row.names = FALSE)
varInfo_final <- getVarInfo("example_varInfo.xlsx")
varInfo_final2 <- inferLayout(varInfo_final, GADSdat = dat,
inputForDescriptives = inputForDescriptives_edited)#> Var.Name in.DS.und.SH Unterteilung.im.Skalenhandbuch Layout LabelSH
#> 1 Sepal_Length ja NA - <NA>
#> 2 Sepal_Width ja NA - <NA>
#> 3 Petal_Length ja NA - <NA>
#> 4 Petal_Width ja NA - <NA>
#> 5 Species ja NA - <NA>
#> Anmerkung.Var Gliederung Reihenfolge Titel rekodiert QuelleSH
#> 1 - 1.1 0 Sepal Length nein -
#> 2 - 1.1 0 Sepal Width nein -
#> 3 - 1.2 0 Pepal Length nein -
#> 4 - 1.2 0 Pepal Width nein -
#> 5 - 2.1 0 Species nein -
#> Instruktionen Hintergrundmodell HGM.Reihenfolge HGM.Variable.erstellt.aus
#> 1 - nein - -
#> 2 - nein - -
#> 3 - nein - -
#> 4 - nein - -
#> 5 - nein - -
#> intern.extern Seitenumbruch.im.Inhaltsverzeichnis
#> 1 - nein
#> 2 - nein
#> 3 - nein
#> 4 - nein
#> 5 - neinStructure
A key element of the eatCodebook package is that various
forms of variable information can be supplied.
struc <- createStructure(varInfo_final)
head(struc)
#> Titel Ebene
#> 1.1 NA 1
#> 1.2 NA 1.1
#> 1.3 NA 1.2
#> 2.1 NA 2
#> 2.2 NA 2.1
writeExcel(struc, "example_struc.xlsx", row.names = FALSE)
struc_final <- getStructure("example_struc.xlsx")#> Titel Ebene
#> 1 Metrics 1
#> 2 <NA> 1.1
#> 3 <NA> 1.2
#> 4 Species Information 2
#> 5 <NA> 2.1Scale Information
A key element of the eatCodebook package is that various
forms of variable information can be supplied.
scaleInfo <- createScaleInfo(inputForDescriptives_edited)
head(scaleInfo)
#> [1] varName Quelle Anzahl_valider_Werte
#> [4] Items_der_Skala
#> <0 rows> (or 0-length row.names)
writeExcel(scaleInfo, "example_scaleInfo.xlsx", row.names = FALSE)
scaleInfo_final <- getScaleInfo("example_scaleInfo.xlsx")#> [1] varName Quelle Anzahl_valider_Werte
#> [4] Items_der_Skala
#> <0 rows> (or 0-length row.names)Meta data
Meta data can be added to the codebook.
meta <- createMetadata()
meta[1, "Title"] <- "Codebook Test"
meta[1, "Author"] <- "Anna Muster"
meta[1, "Keywords"] <- "lsa, education"
meta[1, "Subject"] <- "test"
writeExcel(meta, "example_meta.xlsx", row.names = FALSE)
meta_final <- makeMetadata("example_meta.xlsx")Chapters
Create the chapter structure.
chapters <- createChapters(varInfo_final2)
chapters[1, 2] <- "Iris Datensatz"Codebok
Now we create the actual codebook script via calling the
codebook() function.
latex_skript <- codebook(varInfo = varInfo_final2, missings = miss_final, struc = struc_final,
scaleInfo = scaleInfo_final, dat = eatGADS::extractData(dat),
Kennwertedatensatz = descStatistics, chapters = chapters)
#>
#> Erstelle Layout-Skripte fuer: dat
#> Layout der Variable: Sepal_Length
#> Warning in Latex.length(sections.var1[d], FALSE, FALSE): Fuer folgende Zeichen
#> gibt es keine Laengenangaben: NA. Die Laenge von NA in Latex wird daher
#> unterschaetzt.
#> Layout der Variable: Sepal_Width
#> Layout der Variable: Petal_Length
#> Warning in Latex.length(sections.var1[d], FALSE, FALSE): Fuer folgende Zeichen
#> gibt es keine Laengenangaben: NA. Die Laenge von NA in Latex wird daher
#> unterschaetzt.
#> Layout der Variable: Petal_Width
#> Layout der Variable: Species
#> Warning in Latex.length(sections.var1[d], FALSE, FALSE): Fuer folgende Zeichen
#> gibt es keine Laengenangaben: NA. Die Laenge von NA in Latex wird daher
#> unterschaetzt.Save the Codebok
The resulting object and the meta data are then separately save to the hard drive. Both objects should be saved into the same folder.
write.table(latex_skript , file = "minimal_example.tex" , fileEncoding="UTF-8" ,
col.names=FALSE , row.names=FALSE , quote = FALSE )
write.table(meta_final , file = "minimal_example_meta.xmpdata", fileEncoding="UTF-8" ,
col.names=FALSE , row.names=FALSE , quote = FALSE )Compilation
The LaTeX script for the codebook has now been saved to
the hard drive. This file should now be opened via a
Tex-Editor and simply compiled. Sometimes multiple
consecutive compilation steps are required for a clean output.
Alternatively, the document can be compiled from within R,
for example via tools::texi2pdf().