Quadratic inference functions in marginal models for longitudinal data.
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.
Song
Peter X-K
PX
Department of Biostatistics, UM School of Public Health, University of Michigan, 1420 Washington Heights, Ann Arbor, MI 48109-2029, USA. pxsong@umich.edu
Jiang
Zhichang
Z
Park
Eunjoo
E
Qu
Annie
A
D000927:Anticonvulsants / Q000627:therapeutic use; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D006801:Humans; D008137:Longitudinal Studies; D015233:Models, Statistical; D012640:Seizures / Q000188:drug therapy / Q000517:prevention & control; D012984:Software; D005680:gamma-Aminobutyric Acid / Q000031:analogs & derivatives / Q000627:therapeutic use
D000927:Anticonvulsants; C017985:progabide; D005680:gamma-Aminobutyric Acid