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Changelog

gsm.studykri 0.3.1

  • Analyze_StudyKRI_PredictBoundsRef() now gracefully handles heterogeneous KRI availability across reference studies. When a reference study has no data for a given KRI, it is skipped with a warning instead of causing an error (#9).

gsm.studykri 0.3.0

  • Established compatibility with snowflake backend by:
  • Added vDbIntRandomRange parameter to bootstrap functions (Analyze_StudyKRI_PredictBounds(), Analyze_StudyKRI_PredictBoundsRef(), Analyze_StudyKRI_PredictBoundsRefSet()) to support database backends that use large integer values for random number generation (e.g., Snowflake) (#7)
  • Added nMinGroups parameter to Analyze_StudyKRI_PredictBoundsRefSet() to allow passing pre-calculated minimum group counts, avoiding expensive collect() operations on database backends
  • Added strMinGroupsCol parameter to Analyze_StudyKRI_PredictBoundsRef() to specify custom column name for minimum group counts in StudyRef tables (default: “MinGroups”)
  • Added bSkipValidation parameter to JoinKRIByDenominator() to disable validation checks that require collect() operations for improved performance with database backends
  • Revised reference calculation now creating study-level timelines for each bootstrap iteration before calculating confidcence intervalls. introduced bMixStudies: FALSE this better conserves inter-study variability leading to wider reference confidence intervalls.
  • Fixed Bug that mixed patients with identical subject ids between studies in Input_CountSiteByMonth
  • dfSubjects from Input_CountSiteByMonth() is optional when strGroupCol already in dfNumerator and dfDenominator
  • HandleLazyTables will use unique names for temp tables using random integers
  • remove seed parameter for bootstrap functions
  • add funCompute paramter to Analyze_StudyKRI_PredictBoundsRef which allows to create temporary tables for each reference set to solve backend issues

gsm.studykri 0.2.0

  • Added 10 additional KRI workflows (kri0005-kri0014) covering lab abnormalities, discontinuations, queries, data quality, screening failures, and I/E violations
  • More carefull month to denominator matching for KRI with same denominator
  • better implementation fo vMinDenominator to define minimal Denominator count to define start of study timeline

gsm.studykri 0.1.0

  • Initial release
  • Bootstrap-based study-level KRI confidence intervals
  • 4 base KRI workflows (AE, SAE, PD, IPD)
  • Portfolio simulation capabilities