Bayesian analysis of clustered interval-censored data

J Dent Res. 2005 Sep;84(9):817-21. doi: 10.1177/154405910508400907.

Abstract

The recording of multiple interval-censored failure times is common in dental research. Modeling multilevel data has been a difficult task. This paper aims to use the Bayesian approach to analyze a set of multilevel clustered interval-censored data from a clinical study to investigate the effectiveness of silver diamine fluoride and sodium fluoride varnish in arresting active dentin caries in Chinese pre-school children. The time to arrest dentin caries on a surface was measured. A three-level random-effects Weibull regression model was used. Analysis was performed with WinBUGS. Results revealed a strong positive correlation (0.596) among the caries lesions' arrest times on different surfaces from the same child. The software WinBUGS made the above complicated estimation simple. In conclusion, the annual application of silver diamine fluoride on caries lesions, and caries removal before the application, were found to shorten the arrest time.

Publication types

  • Clinical Trial
  • Randomized Controlled Trial
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Bayes Theorem
  • Cariostatic Agents / administration & dosage*
  • Child, Preschool
  • Cluster Analysis
  • DMF Index
  • Dental Caries / therapy*
  • Dental Cavity Preparation
  • Dentin
  • Female
  • Fluorides, Topical / administration & dosage*
  • Humans
  • Male
  • Markov Chains
  • Monte Carlo Method
  • Outcome Assessment, Health Care / methods*
  • Prospective Studies
  • Quaternary Ammonium Compounds / administration & dosage*
  • Regression Analysis
  • Silver Compounds
  • Sodium Fluoride / administration & dosage*
  • Software
  • Survival Analysis
  • Time Factors

Substances

  • Cariostatic Agents
  • Fluorides, Topical
  • Quaternary Ammonium Compounds
  • Silver Compounds
  • Sodium Fluoride
  • silver diamine fluoride