4.5 Article

Quadratic inference functions in marginal models for longitudinal data

Journal

STATISTICS IN MEDICINE
Volume 28, Issue 29, Pages 3683-3696

Publisher

WILEY-BLACKWELL
DOI: 10.1002/sim.3719

Keywords

efficiency; GEE; goodness-of-fit; model selection; robustness; SAS macro

Funding

  1. NSF
  2. Direct For Mathematical & Physical Scien
  3. Division Of Mathematical Sciences [0902232] Funding Source: National Science Foundation
  4. Division Of Mathematical Sciences
  5. Direct For Mathematical & Physical Scien [0906660] Funding Source: National Science Foundation

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The quadratic inference function (QIF) is a new statistical methodology developed for the estimation and inference in longitudinal data analysis using marginal models. This method is an alternative to the popular generalized estimating equations approach, and it has several useful properties such as robustness, a goodness-of-fit test and model selection. This paper presents an introductory review of the QIF, with a strong emphasis on its applications. In particular, a recently developed SAS MACRO QIF is illustrated in this paper to obtain numerical results. Copyright (C) 2009 John Wiley & Sons, Ltd.

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