Logistic Regression: A Self-learning Text, Third Edition (Statistics in the Health Sciences)

(vip2019) #1

Objectives Upon completion of this chapter, the learner should be
able to:



  1. State or recognize the procedure used when carrying
    out matching in a given study.

  2. State or recognize at least one advantage and one
    disadvantage of matching.

  3. State or recognize when to match or not to match in a
    given study situation.

  4. State or recognize why attaining validity is not a
    justification for matching.

  5. State or recognize two equivalent ways to analyze
    matched data using stratification.

  6. State or recognize the McNemar approach for
    analyzing pair-matched data.

  7. State or recognize the general form of the logistic
    model for analyzing matched data as anE,V,W-type
    model.

  8. State or recognize an appropriate logistic model for
    the analysis of a specified study situation involving
    matched data.

  9. State how dummy or indicator variables are defined
    and used in the logistic model for matched data.

  10. Outline a recommended strategy for the analysis of
    matched data using logistic regression.

  11. Apply the recommended strategy as part of the
    analysis of matched data using logistic regression.

  12. Describe and/or illustrate two options for assessing
    interaction of the exposure variable with the matching
    variables in anE,V,W-type model.

  13. Describe and/or illustrate when it would be
    appropriate to pool “exchangeable” matched sets.

  14. State and/or illustrate theE,V,Wmodel for matched
    follow-up data.


Objectives 391
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