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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/22836

Title: A comparative study on estimation methods to deal with the endogeneity in linear random-intercept models with an extension
Authors: Rikhtehgaran, Reyhaneh
Kazemi, Iraj
Verbeke, Geert
Issue Date: 2017
Publisher: TAYLOR & FRANCIS LTD
Citation: JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION, 87(1), p. 171-186
Abstract: In this paper, we investigate estimation methods to deal with situations where random intercepts are associated to time-varying covariates in the context of linear mixed models. First, a review of previous ways to deal with this so-called endogeneity issue is presented, then a new method based on shared random effects is proposed. Simulation studies and an empirical example are utilized to assess the performance of our proposed method. It is shown that our new approach is more efficient than most competitors and is robust to the misspecification of the random-effects distributions.
Notes: [Rikhtehgaran, Reyhaneh] Isfahan Univ Technol, Dept Math Sci, Esfahan 8415683111, Iran. [Kazemi, Iraj] Univ Isfahan, Dept Stat, Esfahan 81746, Iran. [Verbeke, Geert] Katholieke Univ Leuven, B-3000 Leuven, Belgium. [Verbeke, Geert] Univ Hasselt, B-3590 Diepenbeek, Belgium.
URI: http://hdl.handle.net/1942/22836
DOI: 10.1080/00949655.2016.1196689
ISI #: 000387252400011
ISSN: 0094-9655
Category: A1
Type: Journal Contribution
Validation: ecoom, 2017
Appears in Collections: Research publications

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