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Misspecification of frailty random effects in a clustered survival data

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  • Kiche J.
  • Oscar Ngesa
  • George Orwa

Abstract

Survival analysis models the time it takes until an event occurs. The prototypical event is death, from which the name survival analysis is derived.Accordingly, each time survival analysis is studied, aspects of some selected rates or reliability of some study are usually considered. Frailty modelling has been used in this study as the statistical tool for analysing the time-event data. Parametric and non-parametric models and the frailty models are tted to help derive the required con-clusions.The impact of misspeci cation of frailty random effects in a survival data using parametric frailty modelling approach were determined during this research study.It is expected that these approaches would produce less bias estimates compared to the results achieved of the estimates when the misspeci cation of the frailty random effects are ignored.Mathematics Subject Classi fication :62H30Keywords: misspeci cation, frailty modeling, clustered data.

Suggested Citation

  • Kiche J. & Oscar Ngesa & George Orwa, 2019. "Misspecification of frailty random effects in a clustered survival data," Journal of Statistical and Econometric Methods, SCIENPRESS Ltd, vol. 8(2), pages 1-1.
    • Handle: RePEc:spt:stecon:v:8:y:2019:i:2:f:8_2_1
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    References listed on IDEAS

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    1. Mohan L. Garg & B. Raja Rao & Carol K. Redmond, 1970. "Maximum‐Likelihood Estimation of the Parameters of the Gompertz Survival Function," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 19(2), pages 152-159, June.
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