The application of a random effects model to censored twin data

I. Chao Liu, Ronghui Xu, Deborah L. Blacker, Garrett Fitzmaurice, Michael J. Lyons, Ming T. Tsuang

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)


The authors propose a random effects model to analyze the latent genetic and environmental effects on determining censored outcomes in twin studies. In this model, six normally distributed random effects are used to describe the correlation within twin pairs. The authors employ a Monte Carlo Expectation-Maximization approach for obtaining maximum likelihood estimates of fixed effects and the variances of random effects. The variances of the random effects are reparameterized to be equivalent to genetic and environmental effects in traditional twin models. The authors illustrate this model using data from the Vietnam Era Twin Registry to explore the magnitude of the genetic influence on twin similarity for the age of onset of alcohol abuse. Our results show genetic factors contribute about one third of twin similarity in the age of onset of alcohol abuse in male twins. The application of this model to twin data is discussed.

Original languageEnglish
Pages (from-to)781-789
Number of pages9
JournalBehavior Genetics
Issue number6
Publication statusPublished - Nov 2005
Externally publishedYes


  • Age of onset
  • Frailty model
  • Random effects
  • Survival analysis
  • Twin studies

ASJC Scopus subject areas

  • Genetics
  • Genetics(clinical)
  • Behavioral Neuroscience
  • General Psychology


Dive into the research topics of 'The application of a random effects model to censored twin data'. Together they form a unique fingerprint.

Cite this