The analysis of left truncated bivariate data using frailty models

Antai Wang, Krishnendu Chandra, Xieyang Jia

Research output: Contribution to journalArticlepeer-review

Abstract

In this paper, we study the properties of frailty models for bivariate data under fixed left truncation. It turns out that the distribution of completely observable pairs is also a member of the Archimedean copula family. We propose a new estimation strategy to analyze this type of data using the corresponding Kendall distribution. A general goodness-of-fit test procedure is then developed for selecting the best model. Our strategies are generalization of the methodologies proposed for left truncated data. We demonstrate our new approaches using simulations and an illustrative example and end our paper with some discussion.

Original languageEnglish (US)
Pages (from-to)847-860
Number of pages14
JournalScandinavian Journal of Statistics
Volume45
Issue number4
DOIs
StatePublished - Dec 2018

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

Keywords

  • Kendall's distribution
  • archimedean copula models
  • frailty models
  • left censored bivariate data

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