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Survival Analysis

In: Foundations of Biostatistics

Author

Listed:
  • M. Ataharul Islam

    (University of Dhaka, ISRT)

  • Abdullah Al-Shiha

    (College of Science, King Saud University, Department of Statistics and Operations Research)

Abstract

InSurvival analysis this chapter, the basic concepts and techniques of analyzing survival dataData are introduced. Different study designs for collecting survival data are discussed, and the corresponding procedures for estimating association between exposure and disease such as relative riskRelative risk or oddsOdds ratio are discussed. Also, the procedures for constructing confidence intervals as well as for testing the hypothesis concerning any association between exposure and disease are highlighted for data from prospective, case-control, and cross-sectional studyCross-sectional study designs. The nonparametric methods of estimating survivor function are shown including the product-limit methodProduct-limit method . The varianceVariance of the estimatorEstimator of survivor function is also obtained, and the log-rank testLog-rank test for comparing two survivor functions is also introduced in this chapter. One of the most widely used models in biostatistical data analysis is the Regression logistic logistic regressionLogistic regression model which is introduced in this chapter with examples. The estimation and test procedures are discussed too. The basic concepts of longitudinal data analysis are discussed, and the proportional hazards modelProportional hazards model is introduced in this chapter with example. A simple method of model checking is also shown.

Suggested Citation

  • M. Ataharul Islam & Abdullah Al-Shiha, 2018. "Survival Analysis," Springer Books, in: Foundations of Biostatistics, chapter 0, pages 373-420, Springer.
    • Handle: RePEc:spr:sprchp:978-981-10-8627-4_11
    DOI: 10.1007/978-981-10-8627-4_11
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