A GLM approach to step-stress accelerated life testing with interval censoring

Jinsuk Lee, Rong Pan

Research output: Contribution to journalArticlepeer-review

9 Scopus citations


In this paper, we present a statistical inference procedure for the step-stress accelerated life testing (SSALT) model with Weibull failure time distribution and interval censoring via the formulation of generalized linear model (GLM). The likelihood function of an interval censored SSALT is in general too complicated to obtain analytical results. However, by transforming the failure time to an exponential distribution and using a binomial random variable for failure counts occurred in inspection intervals, a GLM formulation with a complementary log-log link function can be constructed. The estimations of the regression coefficients used for the Weibull scale parameter are obtained through the iterative weighted least square (IWLS) method, and the shape parameter is updated by a direct maximum likelihood (ML) estimation. The confidence intervals for these parameters are estimated through bootstrapping. The application of the proposed GLM approach is demonstrated by an industrial example.

Original languageEnglish (US)
Pages (from-to)810-819
Number of pages10
JournalJournal of Statistical Planning and Inference
Issue number4
StatePublished - Apr 2012


  • Accelerated life testing
  • Bootstrap method
  • Generalized linear model
  • Proportional hazard model
  • Weibull distribution

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty
  • Applied Mathematics


Dive into the research topics of 'A GLM approach to step-stress accelerated life testing with interval censoring'. Together they form a unique fingerprint.

Cite this