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Size and Power of Tests of Hypotheses on Survival Parameters from the Lindley Distribution with Covariates

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Abstract

The Lindley model is considered as an alternative model facilitating analyses of time-to-event data with covariates. Covariate information is incorporated using the Cox’s proportional hazard model with the Lindley model at the timedependent component. Simulation studies are performed to assess the size and power of tests of hypotheses on parameters arising from maximum likelihood estimators of parameters in the Lindley model. Results are contrasted with that arising from Cox’s partial maximum likelihood estimator. The Linley model is used to analyze a publicly available data set and contrasted with other models.

Original languageAmerican English
JournalAustin Biometrics and Biostatistics
Volume2
StatePublished - Jul 1 2015

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Disciplines

  • Biostatistics
  • Community Health
  • Public Health

Keywords

  • Covariate information
  • Cox's Proportional Hazard model
  • Hazard function
  • Lindley distribution
  • Lindley-Cox model
  • Parametric model

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