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Statistical Survival Analysis with Applications

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Book cover Springer Handbook of Engineering Statistics

Part of the book series: Springer Handbooks ((SHB))

Abstract

This chapter discusses several important and interesting applications of statistical survival analysis which are relevant to both medical studies and reliability studies. Although it seems to be true that the proportional hazards models have been more extensively used in the application of biomedical research, the accelerated failure time models are much more popular in engineering and reliability research. Through several applications, this chapter not only offers some unified approaches to statistical survival analysis in biomedical research and reliability/engineering studies, but also sets up necessary connections between the statistical survival models used by biostatisticians and those used by statisticians working in engineering and reliability studies. The first application is the determination of sample size in a typical clinical trial when the mean or a certain percentile of the survival distribution is to be compared. The approach to the problem is based on an accelerated failure time model and therefore can have direct application in designing reliability studies to compare the reliability of two or more groups of differentially manufactured items. The other application we discuss in this chapter is the statistical analysis of reliability data collected from several variations of step-stress accelerated life test. The approach to the problem is based on the accelerated failure time model, but we will point out that these methodologies can be directly applied to medical and clinical studies when different doses of a therapeutic compound are administered in a sequential order to experimental subjects.

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Abbreviations

MLE:

maximum likelihood estimation

MME:

method of moment estimates

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Author information

Authors and Affiliations

  1. Division of Biostatistics, Washington University in St. Louis, 660 South Euclid Avenue, Box 8067, 63110, St. Louis, MO, USA

    Chengjie Xiong

  2. School of Management, China University of Geosciences, No. 388 Lumo Road, 430074, Wuhan, Peoples Republic of China

    Kejun Zhu

  3. Division of Biostatistics, Washington University in St. Louis, School of Medicine, Box 8067, 63110, St. Louis, MO, USA

    Kai Yu

Authors
  1. Chengjie Xiong
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  2. Kejun Zhu
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  3. Kai Yu
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Corresponding authors

Correspondence to Chengjie Xiong , Kejun Zhu or Kai Yu .

Editor information

Editors and Affiliations

  1. Department of Industrial and Systems Engineering, Rutgers the State University of New Jersey, 96 Frelinghuysen Road, 08854, Piscataway, NJ, USA

    Hoang Pham Prof.

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© 2006 Springer-Verlag

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Xiong, C., Zhu, K., Yu, K. (2006). Statistical Survival Analysis with Applications. In: Pham, H. (eds) Springer Handbook of Engineering Statistics. Springer Handbooks. Springer, London. https://doi.org/10.1007/978-1-84628-288-1_19

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  • DOI: https://doi.org/10.1007/978-1-84628-288-1_19

  • Publisher Name: Springer, London

  • Print ISBN: 978-1-85233-806-0

  • Online ISBN: 978-1-84628-288-1

  • eBook Packages: EngineeringEngineering (R0)

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