Download Advances in Survival Analysis by N. Balakrishnan, C.R. Rao PDF

By N. Balakrishnan, C.R. Rao

ISBN-10: 0444500790

ISBN-13: 9780444500793

Handbook of facts: Advances in Survival research covers all vital issues within the quarter of Survival research. every one subject has been lined through a number of chapters written via across the world popular specialists. every one bankruptcy presents a finished and up to date evaluate of the subject. numerous new illustrative examples were used to illustrate the methodologies built. The ebook additionally contains an exhaustive checklist of significant references within the sector of Survival Analysis.

  • Includes updated stories on many vital topics
  • Chapters written via many the world over well known experts
  • Some Chapters supply thoroughly new methodologies and analyses
  • Includes a few new facts and techniques of examining them

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Additional resources for Advances in Survival Analysis

Sample text

Report 86 (2). L. (2003). Survival Analysis: Techniques for Censored and Truncated Data, 2nd edn. Springer, New York. , Schumacher, M. (1996). Evaluating the effect of optimized cutoff values in the assessment of prognostic factors. Comput. Statist. Data Anal. 21, 307–326. , Schumacher, M. (1992). Maximally selected rank statistics. Biometrics 48, 73–85. , Siegmund, D. (1982). Maximally selected chi-square statistics. Biometrics 38, 1011–1016. , Schumacher, M. (1994). Outcome oriented cutpoints in analysis of quantitative exposures.

1 Like. 8 200 0 20 40 98. 5) Ln(2) % Continuous model Cen Score Wald Like. 1 Like. 0 3. Extensions of Contal and O’Quigley’s approach In this section, we presented two extensions of Contal and O’Quigley’s correction. 1, is an extension of the approach to the accelerated failure time model with single continuous covariate. This extension is based on the score statistics for that model. 2). These extensions are based on applying the correction to residuals that are based on the adjustment for other covariates.

T. 5) Ln(2) % Continuous model Jespersen Cen Score Wald Like. 1 Like. 5) Ln(2) % Continuous model Jespersen Contal and O’Quigley Lausen and Schumacher Cen Score Wald Like. 1 Like. 8 200 0 20 40 98. 5) Ln(2) % Continuous model Cen Score Wald Like. 1 Like. 0 3. Extensions of Contal and O’Quigley’s approach In this section, we presented two extensions of Contal and O’Quigley’s correction. 1, is an extension of the approach to the accelerated failure time model with single continuous covariate. This extension is based on the score statistics for that model.

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Advances in Survival Analysis by N. Balakrishnan, C.R. Rao


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