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:: Volume 11, Issue 2 (3-2018) ::
JSS 2018, 11(2): 219-240 Back to browse issues page
Influence Diagnostics in Semiparametric Linear Mixed Measurement Error Models
Hadi Emami * , Parvaneh Mansoori
Abstract:   (5660 Views)

Semiparametric linear mixed measurement error models are extensions of linear mixed measurement error models to include a nonparametric function of some covariate. They have been found to be useful in both cross-sectional and longitudinal studies. In this paper first we propose a penalized corrected likelihood approach to estimate the parametric component in semiparametric linear mixed measurement error model and then using the case deletion and subject deletion analysis we survey the influence diagnostics in such models. Finally, the performance of our influence diagnostics methods are illustrated through a simulated example and a real data set.

Keywords: Case Deletion, Cook's Distance, Corrected Score Methods, Linear Mixed Models, Measurement Error, Semiparametric Linear Models
Full-Text [PDF 256 kb]   (1676 Downloads)    
Type of Study: Applied | Subject: Theoritical Statistics
Received: 2017/01/31 | Accepted: 2018/02/19 | Published: 2018/04/15
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Emami H, Mansoori P. Influence Diagnostics in Semiparametric Linear Mixed Measurement Error Models. JSS 2018; 11 (2) :219-240
URL: http://jss.irstat.ir/article-1-524-en.html

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Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Volume 11, Issue 2 (3-2018) Back to browse issues page
مجله علوم آماری – نشریه علمی پژوهشی انجمن آمار ایران Journal of Statistical Sciences

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