Survival Analysis: Mean Time Between Failures, Statistical Assembly, Reliability Engineering, Log-Logistic Distribution, Weibull Distribu

Overview

Purchase includes free access to book updates online and a free trial membership in the publisher's book club where you can select from more than a million books without charge. Chapters: Mean Time Between Failures, Statistical Assembly, Log-Logistic Distribution, Weibull Distribution, Survival Analysis, Failure Rate, Prognostics, Reliability Theory of Aging and Longevity, Fides, Exponential-Logarithmic Distribution, Logrank Test, Proportional Hazards Models, Accelerated Failure Time Model, Censoring, ...

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Overview

Purchase includes free access to book updates online and a free trial membership in the publisher's book club where you can select from more than a million books without charge. Chapters: Mean Time Between Failures, Statistical Assembly, Log-Logistic Distribution, Weibull Distribution, Survival Analysis, Failure Rate, Prognostics, Reliability Theory of Aging and Longevity, Fides, Exponential-Logarithmic Distribution, Logrank Test, Proportional Hazards Models, Accelerated Failure Time Model, Censoring, Kaplan-meier Estimator, Exponentiated Weibull Distribution, Common Mode Failure, Hazard Ratio, First-Hitting-Time Model, Reliability Theory, Orthogonal Array Testing, Survival Function, Nelson-aalen Estimator, Time-Varying Covariate, Poly-Weibull Distribution, Maintenance-Free Operating Period, Lusser's Law. Excerpt: In the statistical area of survival analysis , an accelerated failure time model ( AFT model ) is a parametric model that provides an alternative to the commonly-used proportional hazards models . Whereas a proportional hazards model assumes that the effect of a covariate is to multiply the hazard by some constant, an AFT model assumes that the effect of a covariate is to multiply the predicted event time by some constant. AFT models can be therefore be framed as linear models for the logarithm of the survival time. Comparison with proportional hazard models The biggest difference is that AFT models are always fully parametric, i.e. a probability distribution must be specified, as there is no known equivalent of Cox 's semi-parametric proportional hazards model. The choice of origin from which to measure time at risk is important in all parametric survival models. Unlike proportional hazards models, the regression parameter estimates from AFT models are robust to omitted covariates . They are also less affected by the choice of probability distribution. The results of AFT models are easily interpreted. For example, the results of a clinical trial with ...

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Product Details

  • ISBN-13: 9781155496931
  • Publisher: General Books LLC
  • Publication date: 5/4/2010
  • Pages: 108
  • Product dimensions: 7.44 (w) x 9.69 (h) x 0.22 (d)

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Sort by: Showing 1 Customer Reviews
  • Anonymous

    Posted May 3, 2013

    I didn't notice the wikipedia reference when I bought this book.

    I didn't notice the wikipedia reference when I bought this book.  The book is about 132 pages, 100 of them are blank. The whole 32 pages of text are simply topics copied from the online wikipedia. Most of the equations are very difficult to read, and there is little to no explanations of theory or applications.  In general, this book is little more than a brief review and introduction to the topics of reliability statistics.  I would not recommend this publication. 

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