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A note on the identifiability of latent variable models for mixed longitudinal data

Author

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  • Tabrizi, Elham
  • Samani, Ehsan Bahrami
  • Ganjali, Mojtaba

Abstract

In the present study, the identifiability problem is considered for a general form of the joint model for two types of responses. The presented three theorems make it easier to verify identifiability. The ideas or techniques from the proofs can be used to extend the work to other joint models.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:stapro:v:167:y:2020:i:c:s0167715220301851
    DOI: 10.1016/j.spl.2020.108882
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    References listed on IDEAS

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    1. 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.
    2. Wang Miao & Peng Ding & Zhi Geng, 2016. "Identifiability of Normal and Normal Mixture Models with Nonignorable Missing Data," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(516), pages 1673-1683, October.
    3. Cui, Xia & Guo, Jianhua & Yang, Guangren, 2017. "On the identifiability and estimation of generalized linear models with parametric nonignorable missing data mechanism," Computational Statistics & Data Analysis, Elsevier, vol. 107(C), pages 64-80.
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    Cited by:

    1. Zhale Tahmasebinejad, 2024. "Analysis of Two - Part Random Effects Model for Semi-Ordinal Longitudinal Response," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 86(2), pages 777-808, November.

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