Local influence in estimating equations

Venezuela, Maria Kelly; Sandoval, Mônica C.; Botter, Denise Aparecida

doi:10.1016/j.csda.2010.10.020

Cited by 15 publications

(12 citation statements)

References 14 publications

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“…Nevertheless, more research is needed for residual analysis for GLMM as already indicated in Dean and Nielsen (2007). Diagnostic tools for the GEE are presented, for example, in Venezuela et al (2007), Venezuela et al (2011), andVens andZiegler (2011) to detect influential and outlying observations using the projection (hat) matrix, Cook's distance, standardized residuals, and half-normal plots of absolute residuals with simulated envelopes, the latter only for constant scale parameter as proposed in Park and Shin (1998). Some diagnostic tools and references are presented in Table 5.…”

Section: Discussionmentioning

confidence: 99%

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Competing regression models for longitudinal data

2012

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The choice of an appropriate family of linear models for the analysis of longitudinal data is often a matter of concern for practitioners. To attenuate such difficulties, we discuss some issues that emerge when analyzing this type of data via a practical example involving pretest-posttest longitudinal data. In particular, we consider log-normal linear mixed models (LNLMM), generalized linear mixed models (GLMM), and models based on generalized estimating equations (GEE). We show how some special features of the data, like a nonconstant coefficient of variation, may be handled in the three approaches and evaluate their performance with respect to the magnitude of standard errors of interpretable and comparable parameters. We also show how different diagnostic tools may be employed to identify outliers and comment on available software. We conclude by noting that the results are similar, but that GEE-based models may be preferable when the goal is to compare the marginal expected responses.

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Section: Discussionmentioning

confidence: 99%

“…Plots of the studentized residuals are discussed in Venezuela et al (2007Venezuela et al ( , 2011 as well as Vens and Ziegler (2011). These residuals are presented in Fig.…”

Section: Analysis Via Gee-based Modelsmentioning

confidence: 99%

Competing regression models for longitudinal data

2012

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“…A similar study was carried out to illustrate measures of local influence by Venezuela et al (2011). First, it presents the results of simulations carried out to examine whether known high-leverage and influential points are determined by the proposed measures.…”

Section: Simulationsmentioning

confidence: 99%

“…In particular, they considered the projection (hat) matrix, Cook's distance, standardized residuals, and half-normal probability plots with simulated envelopes (see Atkinson, 1985). Rather than following the case-deletion approach, Jung (2008) and Venezuela et al (2011) introduced a local influence method to investigate the influence of subjects or observations on GEE regression coefficients. Pan (2001) proposed a modified version (QIC) of Akaike's information criterion that works well for variable and working correlation-matrix selection.…”

Section: Introductionmentioning

confidence: 99%

Influence measures based on the volume of confidence ellipsoids for GEE

Pardo

Sanz²

2012

Biometrical J

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The generalized estimating equations (GEE) derived by Liang and Zeger to analyze longitudinal data have been used in a wide range of medical and biological applications. To make regression a useful and meaningful statistical tool, emphasis should be placed not only on inference or fitting, but also on diagnosing potential data problems. Most of the usual diagnostics for linear regression models have been generalized for GEE. However, global influence measures based on the volume of confidence ellipsoids are not available for GEE analysis. This article presents an extension of these measures that is valid for correlated-measures regression analysis using GEEs. The proposed measures are illustrated by an analysis of epileptic seizure count data arising from a study of prograbide as an adjuvant therapy for partial seizures and some simulated data sets.

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“…Outras propostas para a detecção de observações influentes podem ser encontradas em Preisser e Qaqish [1996] e Pardo e Alonso [2012], por exemplo. Além disso, uma proposta sobre influência local pode ser encontrada em Venezuela et al [2011].…”

Section: Técnicas De Diagnósticounclassified

Avaliação de técnicas de diagnóstico para a análise de dados com medidas repetidas

Kurusu¹

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AgradecimentosPrimeiramente gostaria de agradecer a todos os meus familiares. Em especial aos meus pais, que me apoiaram e estiveram sempre do meu lado.À minha irmã Renata por participar diretamente ao assistirà minha defesa. Ao meu irmão Rafael juntamente com a Mary, que me ajudaram bastante mesmo estando tão longe.As professoras Denise Aparecida Botter e Mônica Carneiro Sandoval, pela orientação, dedicação e paciência que tiveram comigo durante todo esse tempo. Foiótimo ter tido a oportunidade de trabalhar novamente com as duas.Aos professores da banca, Viviana Giampaoli e Juvêncio Santos Nobre, pelas críticas, elogios e sugestões que me ajudaram a finalizar o meu trabalho da melhor maneira possível. Ao colega Roberto Manghi que, da mesma forma que o Juvêncio, disponibilizou as rotinas do R utilizadas em seu trabalho.Aos professores e funcionários do IME que participaram diretamente da minha formação desde os tempos da graduação. Assim como os amigos que fiz durante esse período na USP. Eu considero um privilégio poder ter convivido e aprendido com essas pessoas.Aos colegas de trabalho que me acompanharam durante a parte final dessa jornada.Por fim, agradeçoà CAPES pelo apoio financeiro durante parte desse período.i ii ResumoAvaliação de técnicas de diagnóstico para a análise de dados com medidas repetidas Dentre as possíveis propostas encontradas na literatura estatística para analisar dados oriundos de estudos com observações correlacionadas, estão os modelos condicionais e os modelos marginais. Diversas técnicas têm sido propostas para a análise de diagnóstico nesses modelos.O objetivo deste trabalhoé apresentar algumas das técnicas de diagnóstico disponíveis para os dois tipos de modelos e avaliá-las por meio de estudos de simulação. As técnicas apresentadas também foram aplicadas em um conjunto de dados reais.Palavras-chave: equações de estimação generalizadas, medidas repetidas, modelos condicionais, modelos lineares generalizados hierárquicos, modelos lineares generalizados mistos, modelos lineares mistos, modelos marginais, técnicas de diagnóstico.iii iv Abstract Evaluation of diagnostic techniques for the analysis of data with repeated measuresConditional and marginal models are among the possibilities in statistical literature to analyze data from studies with correlated observations. Several techniques have been proposed for diagnostic analysis in these models. The objective of this work is to present some of the diagnostic techniques available for both modeling approaches and to evaluate them by simulation studies. The presented techniques were also applied in a real dataset.Keywords: conditional models, diagnostic techniques, generalized estimating equations, generalized linear mixed models, hierarchical generalized linear models, linear mixed models, marginal models, repeated measures. Em diversas situações práticas, são frequentes estudos que consideram mais de uma observacão da variável resposta para cada unidade experimental, o que caracteriza um experimento com medidas repetidas. Nessa sit...

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Local influence in estimating equations

Cited by 15 publications

References 14 publications

Competing regression models for longitudinal data

Competing regression models for longitudinal data

Influence measures based on the volume of confidence ellipsoids for GEE

Avaliação de técnicas de diagnóstico para a análise de dados com medidas repetidas

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