Global and local tests to assess stationarity of Markov transition models. Issue 4 (21st April 2019)

• Record Type: Journal Article
• Authors: Rodrigues de Lara, Idemauro Antonio; Hinde, John; Taconeli, Cesar Augusto
• Is Part Of: Communications in statistics. Volume 48:Issue 4(2019)
• Page Start: 1019
• Page End: 1039
• Publication Date: 2019-04-21
• Subjects: Generalized linear models -- Longitudinal categorical data -- Simulation study -- transition probabilities; 62F03 -- 62J12; Mathematical statistics -- Periodicals; Mathematical statistics -- Data processing -- Periodicals; Digital computer simulation -- Periodicals; 519.5
• DOI: 10.1080/03610918.2017.1406504
• Languages: English
• ISSNs: 0361-0918

Abstract

ABSTRACT: We present global and local likelihood-based tests to evaluate stationarity in transition models. Three motivational studies are considered. A simulation study was carried out to assess the performance of the proposed tests. The results showed that they present good performance with the control of the type-I error, especially for ordinal responses, and control of the type-II error, especially for the nominal case. Asymptotically they are close to the classical test performance. They can be executed in a single framework without the need to estimate the transition probabilities, incorporating both categorical and continuous covariates, and used to identify sources of non-stationarity.