4.5 Article

Quadratic inference functions in marginal models for longitudinal data

期刊

STATISTICS IN MEDICINE
卷 28, 期 29, 页码 3683-3696

出版社

WILEY-BLACKWELL
DOI: 10.1002/sim.3719

关键词

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

资金

  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

向作者/读者索取更多资源

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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