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CDISC-SDTM

COURSES WE OFFER CDISC-SDTM

  • Introduction
  • Fundamentals of SDTM
  • Submitting Data in Standard Format
  • Assumption for Domain Models

STUDY DATA TABULATION MODEL (SDTM):

  • INTRODUCTION TO SDTM
  • CRF ANNOTATION
  • MAPPING SPECIFICATIONS
  • SDTM PROGRAMMING

SUBMITTING DATA IN STANDARD FORMAT:

  • Standard Metadata for Dataset Contents and Attributes
  • Using the CDISC Domain Models in Regulatory Submissions - Dataset METADATA
  • Primary Keys
  • CDISC Submission Value-Level Metadata
  • conformance
  • MODELS FOR SPECIAL-PURPOSE DOMAINS:

    • Demographics
    • Comments
    • Subject Elements
    • Subject Visits

    DOMAIN MODELS BASED ON THE GENERAL OBSERVATION CLASSES:

    • Interventions
    • Events
    • Findings
    • Findings about

    TRIAL DESIGN DATA SETS:

    • Introduction
    • Trial Arms
    • Trial Elements
    • Trial Visits
    • Trial Inclusion/Exclusion Criteria
    • Trial Summary Information
    • How to Model the Design of a Clinical Trial

    REPRESENTING RELATIONSHIPS AND DATA:

    • Relating Group of Records Within a Domain Using the Grpid Variable
    • Relating Peer Records
    • Relating Datasets
    • Relating Non-Standard Variables Values to a Parent Domain
    • Relating Comments to A Parent Domain
    • How to Determine where Data Belong in the SDTM
    • Trial Design Datasets
    • Representing Relationships And Data
    • Models for Special Purpose Domains
    • Domain Models Based on General Observation Classes

    FUNDAMENTALS OF THE SDTM:

    • Observations and Variables
    • Datasets and Domains
    • Special-Purpose Datasets
    • The General Observation Classes
    • The SDTM Standard Domain Models
    • Creating a New Domain

ASSUMPTIONS FOR DOMAIN MODELS:
GENERAL ASSUMPTIONS FOR ALL DOMAINS:

  • General Domain Assumptions
  • Review Study Data Tabulation and Implementation Guide
  • Relationship to Analysis Datasets
  • Additional Timing Variables
  • Order of the Variables
  • CDISC Core Variables
  • Additional Guidance on Dataset Naming
  • Splitting Domains
  • Origin Metadata
  • Assigning Natural Keys in the Metadata

GENERAL VARIABLE ASSUMPTIONS:

  • Variable-Naming Conventions
  • Two-Character Domain Identifier
  • Use of "Subject" and USUBJID
  • Case Use of Text in Submitted Data
  • Grouping Variables and Categorization
  • Submitting Free Text from the CRF
  • Multiple Values for a Variable

CODING AND CONTROLLED TERMINOLOGY ASSUMPTIONS:

  • Types of Controlled Terminology
  • Controlled Terminology Text Case
  • Controlled Terminology Values
  • Use of Controlled Terminology and Arbitrary Number Codes
  • Storing Controlled Terminology for Synonym Qualifier Variables
  • Storing Topic Variables for General Domain Models
  • Use of "Yes" and "No" Values

ACTUAL AND RELATIVE TIME ASSUMPTIONS:

  • Formats for Date/Time Variables
  • Formats for Date/Time Variables
  • Intervals of Time and Use of Duration for -DUR Variables
  • Use of the "Study Day" Variables
  • Clinical Encounters and Visits
  • Representing Additional Study Days
  • Use of Relative Timing Variables
  • Date and Time Reported in a Domain Based on Findings
  • Use of Dates as Result Variables
  • Representing Time Points

OTHER ASSUMPTIONS:

  • Original and Standardized Results of Findings and Tests Not Done
  • Linking of Multiple Observations
  • Text Strings That Exceed the Maximum Length for General-Observation-Class Domain Variables
  • Evaluators in the Interventions and Events Observation Classes
  • Clinical Significance for Findings Observation Class Data
  • Supplemental Reason Variables
  • Presence or Absence of Pre-Specified Interventions and Events

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