title: A parametric model for studying organism fitness using step-stress experiments.
abstract: We propose a method based on parametric survival analysis to analyze step-stress data. Step-stress studies are failure time studies in which the experimental stressor is increased at specified time intervals. While this protocol has been frequently employed in industrial reliability studies, it is less common in the life sciences. Possible biological applications include experiments on swimming performance of fish using a step function defining increasing water velocity over time, and treadmill tests on humans. A likelihood-ratio test is developed for comparing the failure times in two groups based on a piecewise constant hazard assumption. The test can be extended to other piecewise distributions and to include covariates. An example data set is used to illustrate the method and highlight experimental design issues. A small simulation study compares this analysis procedure to currently used methods with regard to type I error rate and power.
authors.affiliation: Department of Biostatistics, University of North Carolina at Chapel Hill, North Carolina 27599-7420, USA.
authors.forename: Sonja
authors.initials: S
authors.lastname: Greven
authors.forename: A John
authors.initials: AJ
authors.lastname: Bailer
authors.forename: Lawrence L
authors.initials: LL
authors.lastname: Kupper
authors.forename: Keith E
authors.initials: KE
authors.lastname: Muller
authors.forename: Jeremy L
authors.initials: JL
authors.lastname: Craft
mesh_terms: D000704:Analysis of Variance; D000818:Animals; D001699:Biometry; D005080:Exercise Test / Q000706:statistics & numerical data; D005399:Fishes; D006801:Humans; D016013:Likelihood Functions; D015233:Models, Statistical; D010809:Physical Fitness; D016016:Proportional Hazards Models; D016019:Survival Analysis; D013550:Swimming; D014876:Water Pollution / Q000009:adverse effects