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Trend vector models for the analysis of change in continuous time for multiple groups

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  • de Rooij, Mark

Abstract

A problem with the modeling of repeated multinomial response data is the dimensionality of the response variable. For reducing this dimensionality and enhancing interpretability multidimensional scaling techniques are utilized. The resulting trend vector model provides an easily interpretable graphical display with trajectories of different groups over time. A generalized estimating equations scheme is employed for obtaining estimates of the parameters. Model selection is based on the Bayesian Information Criterion and the bootstrap. For illustration, the model is applied to a data set.

Suggested Citation

  • de Rooij, Mark, 2009. "Trend vector models for the analysis of change in continuous time for multiple groups," Computational Statistics & Data Analysis, Elsevier, vol. 53(8), pages 3209-3216, June.
    • Handle: RePEc:eee:csdana:v:53:y:2009:i:8:p:3209-3216
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    References listed on IDEAS

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    1. Berrie Zielman & Willem Heiser, 1993. "Analysis of asymmetry by a slide-vector," Psychometrika, Springer;The Psychometric Society, vol. 58(1), pages 101-114, March.
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    Cited by:

    1. Blasius, J. & Greenacre, M. & Groenen, P.J.F. & van de Velden, M., 2009. "Special issue on correspondence analysis and related methods," Computational Statistics & Data Analysis, Elsevier, vol. 53(8), pages 3103-3106, June.
    2. Giuseppe Bove & Akinori Okada, 2018. "Methods for the analysis of asymmetric pairwise relationships," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 12(1), pages 5-31, March.
    3. Hsiu-Ting Yu & Mark Rooij, 2013. "Model Selection for the Trend Vector Model," Journal of Classification, Springer;The Classification Society, vol. 30(3), pages 338-369, October.

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