extractData2 {eatGADS}

Extract Data 2

Description

Extract data.frame from a GADSdat object for analyses in R. Per default, missing codes are applied but value labels are dropped. Alternatively, value labels can be selectively applied via labels2character, labels2factor, and labels2ordered. For extracting meta data see extractMeta.

Usage

extractData2(
  GADSdat,
  convertMiss = TRUE,
  labels2character = NULL,
  labels2factor = NULL,
  labels2ordered = NULL,
  dropPartialLabels = TRUE
)

Arguments

GADSdat

A GADSdat object.

convertMiss

Should values tagged as missing values be recoded to NA?

labels2character

For which variables should values be recoded to their labels? The resulting variables are of type character.

labels2factor

For which variables should values be recoded to their labels? The resulting variables are of type factor.

labels2ordered

For which variables should values be recoded to their labels? The resulting variables are of type ordered.

dropPartialLabels

Should value labels for partially labeled variables be dropped? If TRUE, the partial labels will be dropped. If FALSE, the variable will be converted to the class specified in labels2character, labels2factor, or labels2ordered.

Details

A GADSdat object includes actual data (GADSdat$dat) and the corresponding meta data information (GADSdat$labels). extractData2 extracts the data and applies relevant meta data on value level (missing conversion, value labels), so the data can be used for analyses in R. Variable labels are retained as label attributes on column level.

If factor are extracted via labels2factor or labels2ordered, an attempt is made to preserve the underlying integers. If this is not possible, a warning is issued. As SPSS has almost no limitations regarding the underlying values of labeled integers and R's factor format is very strict (no 0, only integers increasing by + 1), this procedure can lead to frequent problems.

Value

Returns a data frame.

Examples

# Extract Data for Analysis
dat <- extractData2(pisa)

# convert only some variables to character, all others remain numeric
dat <- extractData2(pisa, labels2character = c("schtype", "ganztag"))

# convert only some variables to factor, all others remain numeric
dat <- extractData2(pisa, labels2factor = c("schtype", "ganztag"))

# convert all labeled variables to factors
dat <- extractData2(pisa, labels2factor = namesGADS(pisa))

# convert somme variables to factor, some to character
dat <- extractData2(pisa, labels2character = c("schtype", "ganztag"),
                          labels2factor = c("migration"))