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Programming Validation

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Programming Validation

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    1. Programming Validation Presented By Deb Goodfellow, ASG Inc., Cary, NC

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    3. 3 Why do we need validation? Need for accuracy Quality deliverable Errors in programming Different interpretations of requirements

    4. 4 Validation Process For output, check spelling, layout, format, etc. For datasets, variables, formats, lengths, labels, etc.

    5. 5 Useful and necessary tools for validation CRF Protocol SAP Output shells Specs

    6. 6 First steps Check the specs, SAP, CRF to make sure they apply and do not conflict with each other Make sure you have the information required to do the validation

    7. 7 Visual Check Does the output match the shell Are there misspellings in headers, footnotes, titles Is the alignment of columns proper Are any of the data being truncated Are the data formatted correctly

    8. 8 “Spot” checking In some companies, there is no dataset to compare for output. Listings may have hundreds of pages Get clarification on which specific values need to be checked Parallel program and visually check the results

    9. 9 Parallel Programming Independence is necessary Determine which variables are required either by specs or ?? “proc compare” the datasets

    10. 10 Proc compare results All information in the proc compare output is important Note: no unequal values were found. It passes??? Using ID in proc, we match. It passes?

    11. 11 One method for double check We could visually look at all the information in the proc compare results Easy to miss something with all the information given Very time consuming each time you need to re-run

    12. 12 A programming method SASHELP library Dataset VCOLUMN provides information about each dataset Do parallel programming applying the correct formats, labels, lengths, etc according to specs Add a data step to compare

    13. 13 Code Proc sql noprint; Create table production as select distinct Name, length, label, format, informat From sashelp.vcolumn where Memname = “DATAX” and libname = “ADS” Order by Name, length, label, format, informat; Create table validation as select distinct Name, length, label, format, informat From sashelp.vcolumn where Memname = “DATAX” and libname = “WORK” Order by Name, length, label, format, informat; Quit;

    14. Check Data check; merge production(in=a) validation(in=b); by name length label format informat; if a and not b then ds = “prod”; else if b and not a then ds = “val”; else delete; Run;

    15. 15 Overview Validation is more than doing a simple proc compare and getting “No unequal values were found” The more we can check, the more assured we can be of having a quality deliverable Use our programming skills whenever possible to save time and mistakes

    16. 16 Remember There is absolutely no pressure. If you miss something, chances are good that the FDA will find it!

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