In a world of systematic and efficient programming the success of project delivery largely depends on the accuracy of data and implementation of approved standards. The metadata across all the files (analysis/mapping specification file, raw data and final data) need to match for standardization and traceability. CDISC standards for all most all of the data structures clearly states metadata information of a variable, its order of appearance in a dataset, variable length etc. In order to achieve the same metadata as is specified by company or CDISC standard files, programmers need to be very careful while generating the data set at the final stages. Most of time we enter into situations where number of variables are more, or the order or metadata is different from one actually required in the final data set.
Also since these data sets (say SDTM, ADaM) in most cases are developed from SAS coding after referring the analysis/mapping specification file, end moment change in the specification file may not be carried over to these data sets. One approach to limit this error and generate the deliverables per standards is to first develop the analysis/mapping speciation file as per guidelines and then import this file into SAS to create a metadata from these analysis/mapping file. Use these metadata to assign the metadata for final data set. This paper elaborates on the technique of first creating a zero observation data set with the metadata as same as specified in the analysis/mapping specification spreadsheet and then to use this data set to create the final data set. In this approach the analysis/mapping specification file needs to be current and the resulting data sets will be generated as per standard. A review of final data set will double check the metadata consistency not only in the resulting data sets but also on the analysis/mapping specification file.
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