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This function converts a data.frame with data that have been prepared for IRT analyses with eatPrep to an eatGADS object.

Usage

prep2GADS(dat, inputList, trafoType = c("scored", "raw"),
misTypes = list(mvi = -95, mnr = -96, mci = -97, mbd = -94, mir = -98, mbi = -99),
verbose = TRUE)

Arguments

dat

A data.frame, typically one in the last transformation status after eatPrep-based transformations (after 'scoring'). However, merged, recoded and aggregated, but not scored data can also be handled, as long as this data.frames' colnames correspond to the unit-names 'units' in the inputList (that is trafoType=="scored"). Merged but not recoded, not aggregated and not scored data can also be converted to a GADSdat object (using trafoType=="raw").

inputList

A list following the typical structure of an eatPrep inputList. Only the first three data frames are needed to utilize this function. See ‘Details’.

trafoType

Character string. Whether raw data (including original values and subunits) or scored data (usually, 0/1 and mistypes like mbi/mbo et al. and everything aggregated to units) shall be exported.

misTypes

A named list with definitions how to recode the different types of missings (mainly used when trafoType=="scored").

verbose

logical. If TRUE, additional information is printed.

Details

This function converts a recoded, aggregated and scored data set to an eatGADS object using the meta information stored in an inputList. Only the first three data.frames of a typical inputList are used (subunits, values and units). However, the order of these three data.frames in the inputList is irrelevant.

Examples of data frames subunits, values and units can be found via data(inputList).

Value

A GADSdat object.

Author

Karoline Sachse

Examples

data(inputDat)
data(inputList)

prepDatScored <- automateDataPreparation(inputList = inputList, datList = inputDat,
    readSpss = FALSE, checkData=FALSE, mergeData = TRUE, recodeData=TRUE,
    aggregateData=TRUE, scoreData=TRUE, writeSpss=FALSE, verbose = TRUE)
#> Starting automateDataPreparation 2024-09-11 08:53:46.361477
#> 
#> Check has been skipped.
#> 
#> Start merging.
#> Start merging of dataset 1.
#> Start merging of dataset 2.
#> Start merging of dataset 3.
#> Start adding mbd according to data pattern.
#> 
#> Start recoding.
#> 
#> Found no recode information for variable(s): 
#> ID, hisei. 
#> This/These variable(s) will not be recoded.
#> 
#> Variables... I01, I02, I03, I04, I05, I06, I07, I08, I09, I10, I11, I12a, I12b, I12c, I13, I14, I15, I16, I17, I18, I19, I20, I21, I22, I23, I24, I25, I26, I27, I28
#> ...have been recoded.
#> 
#> RecodeMnr has been skipped.
#> 
#> Start aggregating
#> Since inputList$aggrMiss exists, this will be used instead of default.
#> All aggregation rules will be defaulted to 'SUM', because no other type is currently supported.
#> Found 27 unit(s) with only one subunit in 'dat'. This/these subunit(s) will not be aggregated and renamed to their respective unit name(s).
#> 1 units were aggregated: I12.
#> 
#> Start scoring.
#>  1 unit was scored: `I12`.
#> 
#> No SPSS-File has been written.
#> 
#> Missings are UNcollapsed.
#> automateDataPreparation terminated successfully! 2024-09-11 08:53:46.500952

GADSobj1 <- prep2GADS(dat = prepDatScored, inputList = inputList[1:3], trafoType = "scored",
                                verbose=TRUE)
#> 
#> ── Check: Variables without info 
#>  The following 1 variable is not in inputList ($units$unit) but in dataset,
#> its meta data will be set to NA: `hisei`

prepDatRaw <- automateDataPreparation(inputList = inputList, datList = inputDat,
    readSpss = FALSE, checkData=FALSE, mergeData = TRUE, recodeData=FALSE,
    aggregateData=FALSE, scoreData=FALSE, writeSpss=FALSE, verbose = TRUE)
#> Starting automateDataPreparation 2024-09-11 08:53:46.542744
#> 
#> Check has been skipped.
#> 
#> Start merging.
#> Start merging of dataset 1.
#> Start merging of dataset 2.
#> Start merging of dataset 3.
#> Start adding mbd according to data pattern.
#> 
#> Recode has been skipped.
#> 
#> RecodeMnr has been skipped.
#> 
#> Aggregate has been skipped.
#> 
#> Scoring has been skipped.
#> 
#> No SPSS-File has been written.
#> 
#> Missings are UNcollapsed.
#> automateDataPreparation terminated successfully! 2024-09-11 08:53:46.593013

GADSobj2 <- prep2GADS(dat = prepDatRaw, inputList = inputList[1:3], trafoType = "raw",
                                verbose=TRUE)
#> 
#> ── Check: Variables without info 
#>  The following 1 variable is not in inputList ($subunits$subunit or
#> $units$unit) but in dataset, its meta data will be set to NA: `hisei`