A meta-analysis approach for step-stress experiments

• Published in: Journal of statistical planning and inference 2009-09, Vol.139 (9), p.2907-2919
• Main Authors: Kateri, M., Kamps, U., Balakrishnan, N.
• Format: Article
• Language: English
• Subjects: Accelerated life testing; Applications; Conditional moment generating function; Cumulative exposure model; Exact sciences and technology; Exponential distribution; General topics; Mathematics; Maximum likelihood estimation; Nonparametric inference; Probability and statistics; Reliability, life testing, quality control; Sciences and techniques of general use; Statistics; Type-II censoring
• ISSN: 0378-3758; 1873-1171
• DOI: 10.1016/j.jspi.2009.01.013

The step-stress model is a special case of accelerated life testing that allows for testing of units under different levels of stress with changes occurring at various intermediate stages of the experiment. Interest then lies on inference for the mean lifetime at each stress level. All step-stress models discussed so far in the literature are based on a single experiment. For the situation when data have been collected from different experiments wherein all the test units had been exposed to the same levels of stress but with possibly different points of change of stress, we introduce a model that combines the different experiments and facilitates a meta-analysis for the estimation of the mean lifetimes. We then discuss in detail the likelihood inference for the case of simple step-stress experiments under exponentially distributed lifetimes with Type-II censoring.