Forecasting multivariate longitudinal binary data with marginal and marginally specified models

Asar, Özgür and Ilk, Ozlem (2015) Forecasting multivariate longitudinal binary data with marginal and marginally specified models. Journal of Statistical Computation and Simulation, 86 (2). pp. 414-429. ISSN 1563-5163

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Abstract

Forecasting with longitudinal data has been rarely studied. Most of the available studies are for continuous response and all of them are for univariate response. In this study, we consider forecasting multivariate longitudinal binary data. Five different models including simple ones, univariate and multivariate marginal models, and complex ones, marginally specified models, are studied to forecast such data. Model forecasting abilities are illustrated via a real-life data set and a simulation study. The simulation study includes a model independent data generation to provide a fair environment for model competitions. Independent variables are forecast as well as the dependent ones to mimic the real-life cases best. Several accuracy measures are considered to compare model forecasting abilities. Results show that complex models yield better forecasts.

Item Type:
Journal Article
Journal or Publication Title:
Journal of Statistical Computation and Simulation
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/2600/2611
Subjects:
?? comparative studiesdichotomous dataexponential smoothingforecasting competitionsmarginalized modelsmedical statisticsmodelling and simulationapplied mathematicsstatistics and probabilitystatistics, probability and uncertainty ??
ID Code:
72869
Deposited By:
Deposited On:
06 Feb 2015 17:11
Refereed?:
Yes
Published?:
Published
Last Modified:
15 Jul 2024 15:02