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Sensitivity analysis for the identifiability with application to latent random effect model for the mixed data

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  • E. Bahrami Samani

Abstract

In this paper, we study the indentifiability of a latent random effect model for the mixed correlated continuous and ordinal longitudinal responses. We derive conditions for the identifiability of the covariance parameters of the responses. Also, we proposed sensitivity analysis to investigate the perturbation from the non-identifiability of the covariance parameters, it is shown how one can use some elements of covariance structure. These elements associate conditions for identifiability of the covariance parameters of the responses. Influence of small perturbation of these elements on maximal normal curvature is also studied. The model is illustrated using medical data.

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  • E. Bahrami Samani, 2014. "Sensitivity analysis for the identifiability with application to latent random effect model for the mixed data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 41(12), pages 2761-2776, December.
    • Handle: RePEc:taf:japsta:v:41:y:2014:i:12:p:2761-2776
    DOI: 10.1080/02664763.2014.929641
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    Cited by:

    1. Tabrizi, Elham & Samani, Ehsan Bahrami & Ganjali, Mojtaba, 2020. "A note on the identifiability of latent variable models for mixed longitudinal data," Statistics & Probability Letters, Elsevier, vol. 167(C).

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