An alternative method for evaluating stationarity in transition models. Issue 15 (13th October 2017)

• Record Type: Journal Article
• Authors: de Lara, Idemauro Antonio Rodrigues; Hinde, John; Taconeli, Cesar Augusto
• Is Part Of: Journal of statistical computation and simulation. Volume 87:Issue 15(2017)
• Page Start: 2962
• Page End: 2980
• Publication Date: 2017-10-13
• Subjects: Longitudinal categorical data -- transition probabilities -- stationarity -- simulation; 62F03 -- 62J12; Mathematical statistics -- Data processing -- Periodicals; Digital computer simulation -- Periodicals; 519.5028505
• DOI: 10.1080/00949655.2017.1351562
• Languages: English
• ISSNs: 0094-9655

Abstract

ABSTRACT: Transition models are an important framework that can be used to model longitudinal categorical data. A relevant issue in applying these models is the condition of stationarity, or homogeneity of transition probabilities over time. We propose two tests to assess stationarity in transition models: Wald and likelihood-ratio tests, which do not make use of transition probabilities, using only the estimated parameters of the models in contrast to the classical test available in the literature. In this paper, we present two motivating studies, with ordinal longitudinal data, to which proportional odds transition models are fitted and the two proposed tests are applied as well as the classical test. Additionally, their performances are assessed through simulation studies. The results show that the proposed tests have good performance, being better for control of type-I error and they present equivalent power functions asymptotically. Also, the correlations between the Wald, likelihood-ratio and the classical test statistics are positive and large, an indicator of general concordance. Additionally, both of the proposed tests are more flexible and can be applied in studies with qualitative and quantitative covariates.