Peer-Reviewed Journal Details
Mandatory Fields
de Lara, IAR;Hinde, J;Taconeli, CA
2017
January
Journal Of Statistical Computation And Simulation
An alternative method for evaluating stationarity in transition models
Published
()
Optional Fields
LONGITUDINAL DATA CATEGORICAL-DATA ORDINAL DATA REGRESSION INFERENCE OUTCOMES TESTS
87
2962
2980
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.
0094-9655
10.1080/00949655.2017.1351562
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