- life tables (estimate survival functions for grouped survival data)
- Kaplan-Meier plot (estimate survival functions for survival data recorded for individuals)
- Survival function comparison tests (for survival data recorded for individuals, test whether two or more samples are from populations that follow the same survival function: Mantel-Cox log-rank test, Gehan-Breslow test, Tarone-Ware test)
To properly analyze and interpret results of survival analysis, you should be familiar with the following terms and concepts:
If you are not familiar with these terms and concepts, you are advised to consult with a statistician. Failure to understand and properly apply survival analysis may result in drawing erroneous conclusions from your data. Additionally, you may want to consult the following references:
- Cox, D. R. and Oakes, D. 1984. Analysis of Survival Data. London: Chapman and Hall.
- Elandt-Johnson, Regina C. and Johnson, Norman L. 1980. Survival Models and Data Analysis. New York: John Wiley & Sons.
- Kalbfleisch, John D. and Prentice, Ross L. 1980. The Statistical Analysis of Failure Time Data. New York: John Wiley & Sons.
- Lawless, J. F. 1982. Statistical Models and Methods for Lifetime Data. New York: John Wiley & Sons.
- Lee, Elisa T. 1992. Statistical Methods for Survival Data Analysis. 2nd ed. New York: John Wiley & Sons.
- Marubini, Ettore, and Valsecchi, Maria Grazia. 1995. Analysing Survival Data from Clinical Trials and Observational Studies. New York: John Wiley & Sons.
- Miller, Rupert G. Jr. 1981. Survival Analysis. New York: John Wiley & Sons.
- Rosner, Bernard. 1995. Fundamentals of Biostatistics. 4th ed. Belmont, California: Duxbury Press.