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The authors of this monograph have developed a large and important
class of survival analysis models that generalize most of the
existing models. In a unified, systematic presentation, this
monograph fully details those models and explores areas of
accelerated life testing usually only touched upon in the
literature. Accelerated Life Models: Modeling and Statistical
Analysis presents models, methods of data collection, and
statistical analysis for failure-time regression data in
accelerated life testing and for degradation data with explanatory
variables. In addition to the classical results, the authors devote
considerable attention to models with time-varying explanatory
variables and to methods of semiparametric estimation. They also
examine the simultaneous analysis of degradation and failure-time
data when the intensities of failure in different modes depend on
the level of degradation and the values of explanatory variables.
The authors avoid technical details by explaining the ideas and
referring to resources where thorough analysis can be found.
Whether used for teaching, research or general reference,
Accelerated Life Models: Modeling and Statistical Analysis provides
new and known models and modern methods of accelerated life data
analysis.
The authors of this monograph have developed a large and important class of survival analysis models that generalize most of the existing models. In a unified, systematic presentation, this monograph fully details those models and explores areas of accelerated life testing usually only touched upon in the literature.
Accelerated Life Models: Modeling and Statistical Analysis presents models, methods of data collection, and statistical analysis for failure-time regression data in accelerated life testing and for degradation data with explanatory variables. In addition to the classical results, the authors devote considerable attention to models with time-varying explanatory variables and to methods of semiparametric estimation. They also examine the simultaneous analysis of degradation and failure-time data when the intensities of failure in different modes depend on the level of degradation and the values of explanatory variables.
The authors avoid technical details by explaining the ideas and referring to resources where thorough analysis can be found. Whether used for teaching, research or general reference, Accelerated Life Models: Modeling and Statistical Analysis provides new and known models and modern methods of accelerated life data analysis.
This book will be of interest to readers active in the fields of
survival analysis, genetics, ecology, biology, demography,
reliability and quality control. Since Sir David Cox's pioneering
work in 1972, the proportional hazards model has become the most
important model in survival analysis. The success of the Cox model
stimulated further studies in semiparametric and nonparametric
theories, counting process models, study designs in epidemiology,
and the development of many other regression models that could
offer more flexible or more suitable approaches in data analysis.
Flexible semiparametric regression models are increasingly being
used to relate lifetime distributions to time-dependent explanatory
variables. Throughout the book, various recent statistical models
are developed in close connection with specific data from
experimental studies in clinical trials or from observational
studies.
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