Concatenate IQRrmd objects
combine_IQRdataGENERAL.RdConcatenate IQRrmd objects
combine_IQRdataGENERAL( data1, data2, FLAGkeepAllCols = FALSE, FLAGforceOverwriteNLMEcols = TRUE, methodBLOQ = NULL, FLAGforceOverwriteNUMcols = TRUE )
Arguments
| data1 | IQRdataGENERAL object |
|---|---|
| data2 | IQRdataGENERAL object |
| FLAGkeepAllCols | FALSE (default): resulting data object only contains common columns and but all covariate columns. TRUE: resulting dataset contains all columns present in any of the data set. NA imputed for non-common columns. |
| FLAGforceOverwriteNLMEcols | TRUE (default): if NLME columns (see second table above) are present in the dataset they will be overwritten with default values. FALSE: they will not be overwritten and kept as they are - user has to ensure that their contents do make sense! |
| methodBLOQ | Allows specification of the method for handling values below the lower limit of quantification. By default the "M1" method is used. Alternative settings are "M3", "M4", "M5", "M6", and "M7". |
| FLAGforceOverwriteNUMcols | TRUE (default): Overwrites numerical columns (IND, STUDYN, TRT, TRTR) ensuring unique values for corresponding text columns (INDNAME, STUDY, TRTNAME, TRTNAMER) |
Value
Concatenated IQRdataGENERAL object
See also
Other IQRdataGeneral:
+.IQRdataGENERAL(),
IQRcalcTAD(),
IQRdataGENERAL(),
IQRexpandADDLII(),
IQRloadCSVdata(),
IQRsaveCSVdata(),
addIndivRegressors_IQRdataGENERAL(),
addLabel_IQRdataGENERAL(),
attributes0(),
blloqInfo_IQRdataGENERAL(),
blloq_IQRdataGENERAL(),
check_IQRdataGENERAL(),
clean_IQRdataGENERAL(),
convertCat2Text(),
covImpute_IQRdataGENERAL(),
date2dateday_IQRdataProgramming(),
date2datetime_IQRdataProgramming(),
date2time_IQRdataProgramming(),
exportDEFINE_IQRaedataER(),
exportDEFINE_IQRdataGENERAL(),
exportDEFINEpdf_IQRdataGENERAL(),
exportSYS_IQRdataGENERAL(),
export_IQRdataGENERAL(),
getLabels_dataframe(),
getNAcolNLME_IQRdataGENERAL(),
handleSameTimeObs_IQRdataGENERAL(),
is_IQRdataGENERAL(),
loadATRinfo_csvData(),
loadAttributeFile(),
load_IQRdataGENERAL(),
mapCategoricalCovariate_IQRnlmeProject(),
mapCategoricalCovariate_csvData(),
mapContinuousCovariate_IQRnlmeProject(),
mapContinuousCovariate_csvData(),
mutateCov_IQRdataGENERAL(),
obfuscate_IQRdataGENERAL(),
plot.IQRdataGENERAL(),
plotCorCat_IQRdataGENERAL(),
plotCorCovCat_IQRdataGENERAL(),
plotCorCov_IQRdataGENERAL(),
plotCovDistribution_IQRdataGENERAL(),
plotDoseSchedule_IQRdataGENERAL(),
plotIndiv_IQRdataGENERAL(),
plotRange_IQRdataGENERAL(),
plotSampleSchedule_IQRdataGENERAL(),
plotSpaghetti_IQRdataGENERAL(),
print.IQRdataGENERAL(),
removeCommata_dataframe(),
rmAMT0_IQRdataGENERAL(),
rmDosePostLastObs_IQRdataGENERAL(),
rmIGNOREd_IQRdataGENERAL(),
rmMissingTIMEobsRecords_IQRdataGENERAL(),
rmNOobsSUB_IQRdataGENERAL(),
rmNonTask_IQRdataGENERAL(),
rmPLACEBO_IQRdataGENERAL(),
rmSubjects_IQRdataGENERAL(),
setIGNORErecords_IQRdataGENERAL(),
setMissingDVobsRecordsIGNORE_IQRdataGENERAL(),
subset.IQRdataGENERAL(),
summary.IQRdataGENERAL(),
summaryCat_IQRdataGENERAL(),
summaryCov_IQRdataGENERAL(),
summaryObservations_IQRdataGENERAL(),
transformObs_IQRdataGENERAL(),
unlabel_dataframe()