Define.xml: What It Is and Why It Matters
A practical guide to Define-XML for clinical programmers, covering what Define-XML is, why it matters, datasets, variables, codelists, value-level metadata, origins, computational methods, document references, validation, regulatory submission, and practical implementation.
Creating ADTTE: Time-to-Event Analysis Datasets
A practical guide to creating ADTTE time-to-event analysis datasets for clinical trials, including AVAL, CNSR, STARTDT, ADT, PARAMCD, event dates, censoring, derivations, analysis populations, Kaplan-Meier analysis, SAS and R implementation, and quality control.
Creating ADAE: Adverse Event Analysis Datasets
A practical guide to creating ADAE adverse event analysis datasets for clinical trials, including SDTM AE to ADAE derivation, treatment-emergent adverse events, analysis dates, analysis days, severity, seriousness, relationship, occurrence flags, subject-level treatment variables, data structures, derivations, quality control, and R implementation.
Common CDISC Submission Pitfalls
A practical guide to common CDISC regulatory submission pitfalls, including SDTM, ADaM, Define-XML, controlled terminology, traceability, validation findings, metadata, dataset structure, reviewer usability, and submission readiness.
CDISC Controlled Terminology Explained
A practical guide to CDISC Controlled Terminology, including codelists, submission values, extensible terminology, CT packages, SDTM and ADaM implementation, validation, common programming mistakes, and practical examples.
BDS vs. ADaM Dataset Structures
A practical guide to BDS versus other ADaM dataset structures, including ADSL, BDS, OCCDS, one-record-per-subject versus repeated-measures structures, PARAM and PARAMCD, AVAL, BASE, CHG, PCHG, analysis flags, traceability, examples, and SAS and R implementation.
ADaM Dataset Structure Explained
A practical guide to ADaM dataset structure for clinical programmers, including ADSL, BDS, OCCDS, variables, parameters, baseline, analysis values, derivations, traceability, and SAS implementation.
ADSL: The Subject-Level Analysis Dataset
A practical guide to ADSL, the ADaM Subject-Level Analysis Dataset, including subject-level variables, treatment, analysis populations, dates, baseline concepts, disposition, exposure, safety, efficacy, derivations, traceability, and SAS and R implementation.