Literature DB >> 19757486

Quadratic inference functions in marginal models for longitudinal data.

Peter X-K Song1, Zhichang Jiang, Eunjoo Park, Annie Qu.   

Abstract

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.

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Year:  2009        PMID: 19757486     DOI: 10.1002/sim.3719

Source DB:  PubMed          Journal:  Stat Med        ISSN: 0277-6715            Impact factor:   2.373


  10 in total

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6.  An evaluation of quadratic inference functions for estimating intervention effects in cluster randomized trials.

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Journal:  Acta Inform Med       Date:  2018-06

8.  Multivariate partial linear varying coefficients model for gene-environment interactions with multiple longitudinal traits.

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9.  Morphometry Predicts Early GFR Change in Primary Proteinuric Glomerulopathies: A Longitudinal Cohort Study Using Generalized Estimating Equations.

Authors:  Kevin V Lemley; Serena M Bagnasco; Cynthia C Nast; Laura Barisoni; Catherine M Conway; Stephen M Hewitt; Peter X K Song
Journal:  PLoS One       Date:  2016-06-10       Impact factor: 3.240

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  10 in total

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