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Modeling Strategy Guidelines

  • David G. Kleinbaum
  • Mitchel Klein
Chapter
Part of the Statistics for Biology and Health book series (SBH)

Abstract

We begin this chapter by giving the rationale for having a strategy to determine a “best” model. Focus is on a logistic model containing a single dichotomous exposure variable that adjusts for potential confounding and potential interaction effects of covariates considered for control. A strategy is recommended, which has three stages: (1) variable specification, (2) interaction assessment, and (3) confounding assessment followed by consideration of precision. Causal diagrams are introduced as a component of the variable specification stage. The initial model must be “hierarchically well-formulated”, a term to be defined and illustrated. Given an initial model, we recommend a strategy involving a “hierarchical backward elimination procedure” for removing variables. In carrying out this strategy, statistical testing is allowed for assessing interaction terms but is not allowed for assessing confounding. Further description of interaction and confounding assessment is given in the next chapter (Chap. 7).

Keywords

Causal Structure Product Term Elimination Procedure Surgical Wound Infection Causal Diagram 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  1. 1.Department of EpidemiologyEmory University Rollins School of Public HealthAtlantaUSA

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