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Global and local tests to assess stationarity of Markov transition models

Rodrigues de Lara, Idemauro Antonio
; 
Hinde, John
; 
Taconeli, Cesar Augusto
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Identifiers
http://hdl.handle.net/10379/15793
 https://doi.org/10.13025/15186
Publication Date
2018-02-09
Keywords
Mathematics, Longitudinal categorical data, Simulation study, transition probabilities
Type
journal article
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Citation
Rodrigues de Lara, Idemauro Antonio, Hinde, John, & Taconeli, Cesar Augusto. (2019). Global and local tests to assess stationarity of Markov transition models. Communications in Statistics - Simulation and Computation, 48(4), 1019-1039. doi: 10.1080/03610918.2017.1406504
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.
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Taylor & Francis
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CC BY-NC-ND
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