First-order marginalised transition random effects models with probit link function

Asar, Özgür and Ilk, Ozlem (2016) First-order marginalised transition random effects models with probit link function. Journal of Applied Statistics, 43 (5). pp. 925-942. ISSN 0266-4763

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Abstract

Marginalised models, also known as marginally specified models, have recently become a popular tool for analysis of discrete longitudinal data. Despite being a novel statistical methodology, these models introduce complex constraint equations and model fitting algorithms. On the other hand, there is a lack of publicly available software to fit these models. In this paper, we propose a three-level marginalised model for analysis of multivariate longitudinal binary outcome. The implicit function theorem is introduced to approximately solve the marginal constraint equations explicitly. probit link enables direct solutions to the convolution equations. Parameters are estimated by maximum likelihood via a Fisher-Scoring algorithm. A simulation study is conducted to examine the finite-sample properties of the estimator. We illustrate the model with an application to the data set from the Iowa Youth and Families Project. The R package pnmtrem is prepared to fit the model.

Item Type:
Journal Article
Journal or Publication Title:
Journal of Applied Statistics
Additional Information:
This is an Accepted Manuscript of an article published by Taylor & Francis in Journal of Applied Statistics on 11/09/2015, available online: http://wwww.tandfonline.com/doi/abs/10.1080/02664763.2015.1080670
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/1800/1804
Subjects:
ID Code:
75292
Deposited By:
Deposited On:
09 Sep 2015 06:31
Refereed?:
Yes
Published?:
Published
Last Modified:
16 Jul 2020 04:12