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- W2114116842 abstract "Abstract Assuming a nonparametric accelerated failure-time model, a method is proposed for extrapolating low stress-response probabilities on negative-sloping line segments in the stress-failure-time plane. The method (analogous to linear interpolation in dose-response studies) results in simultaneous extrapolation ahead in time and down in stress. In the two-sample (two stress level) setting, a goodness-of-fit test of the nonparametric model is considered and two hypothesis tests are proposed, each pertaining to a condition that (in addition to the assumed model) must be met for the method to be valid. The method is illustrated with censored strand-life data, and some simulated examples are used to consider power and robustness. The failure-time model is a scale family with curvature constraints. The failure probability is assumed to be a sigmoid function of the product of time and a sigmoid scaling function of stress. Time percentiles as functions of stress are assumed to be convex. The goodness-of-fit test is of the Kolmogorov-Smirnov type. Given data at stresses x 1 and x 2, the linear interpolation procedure requires a negative-sloping line such that (a) the failure probability increases along the line as the stress increases from x 1 to x 2, and (b) at the point on the line at x 1 the ratio of the failure probability to time increases in time. A Kolmogorov-Smirnov hypothesis test is used to support (a), and a binomial probability test is used for (b)." @default.
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- W2114116842 date "1988-06-01" @default.
- W2114116842 modified "2023-09-26" @default.
- W2114116842 title "Linear Interpolation with a Nonparametric Accelerated Failure-Time Model" @default.
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- W2114116842 doi "https://doi.org/10.1080/01621459.1988.10478615" @default.
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