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A novel method for joint modeling of survival data and count data for both simple randomized and cluster randomized data

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  • A. A. Sunethra
  • M. R. Sooriyarachchi

Abstract

The objective of this study was to develop an improved analytical solution for analyzing data with correlated survival and count responses for two common designs of simple randomized and cluster randomized data. The proposed joint model was used for analyzing data from a randomized control trial on Epilepsy where the two responses were the timing of seizures and count of seizures. It was identified that the use of the proposed joint model provides better analysis of the data in terms of identifying and quantifying the risk factors for each response variable and predicting the length time without seizures for the Epilepsy patients.

Suggested Citation

  • A. A. Sunethra & M. R. Sooriyarachchi, 2021. "A novel method for joint modeling of survival data and count data for both simple randomized and cluster randomized data," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 50(18), pages 4180-4202, August.
    • Handle: RePEc:taf:lstaxx:v:50:y:2021:i:18:p:4180-4202
    DOI: 10.1080/03610926.2020.1713366
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    Cited by:

    1. Murray, James & Philipson, Pete, 2023. "Fast estimation for generalised multivariate joint models using an approximate EM algorithm," Computational Statistics & Data Analysis, Elsevier, vol. 187(C).

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