Exports an IQRdataGENERAL object as an NLME dataset

This function exports an IQRdataGENERAL object as an NLME dataset. Such an NLME dataset is a CSV file that is suitable for NLME analysis in NONMEM and MONOLIX. The main difference to IQRdataGENERAL datasets is that regression parameters need to be listed in a certain order and that spaces in character strings need to be removed (due to good old NONMEM). Additionally, extra rows with non-doses and non-observations should have been removed before and thus the AE, BASE, and SCREEN related columns are not of much use anymore. During export of an NLME dataset the following is done:

• ADM is set according to the order of doseNAMES!

• Reordering the columns to have the modeling related columns at the beginning and the regression parameters in the defined order at the end of the columns.

• Spaces in non-numeric entries will be replaced by ":::" to allow good old NONMEM to work ...

• Columns "AE","AEGRADE","AESER","AEDRGREL","VALUETXT","BASE","SCREEN" are not present anymore, as not very useful in this NLME setting. In order to support also the changes in MONOLIX 2018 (why do they keep changing everything over and over again ...???) we will do the following changes to the data during export to an NLME dataset:

1. YTYPE: NA for dosing events

2. ADM: NA for observation events

exportSYS_IQRdataGENERAL(
data,
regressorNames = NULL,
doseNAMES = NULL,
obsNAMES = NULL,
filename = NULL,
FLAGxpt = FALSE,
FLAGdefine = TRUE,
FLAGzip = FALSE,
)

exportNLME_IQRdataGENERAL(
data,
regressorNames = NULL,
doseNAMES = NULL,
obsNAMES = NULL,
filename = NULL,
FLAGxpt = FALSE,
FLAGdefine = TRUE,
FLAGzip = FALSE,
)
data IQRdataGENERAL object Vector with names of regression parameter columns (the order of these columns is important and they will be ordered exactly as provided here) Vector with dose record names (= entries in NAME-column) to use during NLME data export. ADM values will be set according to the order of NAMEs in the doseNAMES argument Vector with observation names (= entries in NAME-column) to use during NLME data export. YTYPE values will be set according to the order of NAMEs in the obsNAMES argument Filename of the NLME CSV file to create (not more than 8 characters without extension - if FLAGxpt=TRUE) If TRUE then a SAS XPT file will be generated additionally If TRUE then a define.rmd file will be generated additionally. The syntax of this file is in the IQReport markdown syntax and allows human readbility. The IQReport software can subsequently be used to convert this file to Microsoft WORD, allowing further editing and saving as a PDF file. Please read the documentation for the exportDEFINE_IQRdataGENERAL function to learn more about IQReport. If TRUE then the exported data files (.csv, .atr, .xpt, .docx, .rmd, etc.) will be zipped and placed in the potential path in the "filename" as the filename.dat.zip. Other files will be removed. List with named elements. Names are column names and the value of an element is the label. If defining addColLabels for columns that are already handled automatically, the provided labels will overwrite the automatic ones. Example: addColLabels <- list(IXGDF="Other label",NEWCCOL="Label for NEWCOL"). This information is needed only for XPT and define file generation
Other IQRdataGeneral: +.IQRdataGENERAL(), IQRcalcTAD(), IQRdataGENERAL(), IQRexpandADDLII(), IQRloadCSVdata(), IQRsaveCSVdata(), addIndivRegressors_IQRdataGENERAL(), addLabel_IQRdataGENERAL(), attributes0(), blloqInfo_IQRdataGENERAL(), blloq_IQRdataGENERAL(), check_IQRdataGENERAL(), clean_IQRdataGENERAL(), combine_IQRdataGENERAL(), convertCat2Text(), covImpute_IQRdataGENERAL(), date2dateday_IQRdataProgramming(), date2datetime_IQRdataProgramming(), date2time_IQRdataProgramming(), exportDEFINE_IQRaedataER(), exportDEFINE_IQRdataGENERAL(), exportDEFINEpdf_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()