extractData | R Documentation |
Extract data.frame
from a GADSdat
object for analyses in R
. Value labels can be
selectively applied via defining convertLabels
and covertVariables
.
For extracting meta data see extractMeta
.
extractData(
GADSdat,
convertMiss = TRUE,
convertLabels = c("character", "factor", "numeric"),
convertVariables = NULL,
dropPartialLabels = TRUE
)
GADSdat |
A |
convertMiss |
Should values tagged as missing values be recoded to |
convertLabels |
If |
convertVariables |
Character vector of variables names, which labels should be applied to.
All other variables remain as numeric variables in the data.
If not specified [default], value labels are applied to all variables for which labels are available.
Variable names not in the actual |
dropPartialLabels |
Should value labels for partially labeled variables be dropped?
If |
A GADSdat
object includes actual data (GADSdat$dat
) and the corresponding meta data information
(GADSdat$labels
). extractData
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 convertLabels == "factor"
, 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.
Returns a data frame.
# Extract Data for Analysis
dat <- extractData(pisa)
# convert labeled variables to factors
dat <- extractData(pisa, convertLabels = "factor")
# convert only some variables to factor, all others remain numeric
dat <- extractData(pisa, convertLabels = "factor", convertVariables = c("schtype", "ganztag"))
# convert only some variables to character, all others remain numeric
dat <- extractData(pisa, convertLabels = "factor", convertVariables = c("schtype", "ganztag"))
# schtype is now character
table(dat$schtype)
# schtype remains numeric
table(dat$gender)
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