Download The Statistical Analysis of Failure Time Data, Second by Ross L. Prentice John D. Kalbfleisch PDF

By Ross L. Prentice John D. Kalbfleisch

Content material:
Chapter 1 advent (pages 1–30):
Chapter 2 Failure Time versions (pages 31–51):
Chapter three Inference in Parametric types and comparable issues (pages 52–94):
Chapter four Relative possibility (Cox) Regression versions (pages 95–147):
Chapter five Counting methods and Asymptotic thought (pages 148–192):
Chapter 6 chance building and additional effects (pages 193–217):
Chapter 7 Rank Regression and the speeded up Failure Time version (pages 218–246):
Chapter eight Competing dangers and Multistate versions (pages 247–277):
Chapter nine Modeling and research of Recurrent occasion information (pages 278–301):
Chapter 10 research of Correlated Failure Time info (pages 302–327):
Chapter eleven extra Failure Time info subject matters (pages 328–374):

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Example text

21) and corresponding variances obtained within each of the independent strata. 23) typically has an asymptotic χ distribution. It should be noted that this test will be most sensitive to differences among the ρ + 1 treatment groups that are similar across the strata. Examination of the individual log-rank tests in each of the strata can also provide some insights into possible treatment by strata interactions. This method can provide a valuable means of initial analysis and presentation for many data sets.

U) = N(u) — N(u~). 5. {u) —» oo for all u € (0, fl as η —» oo, it is shown that A(r) ->A(f) and [Λ( )-Λ(/)]/ν(/) ^Λ'(0,1), α 5 ί where —» and —> indicate convergence in probability and convergence in distribution, respectively. 5, where items are placed on test in the ith group at time 0, and let Nu(t),t > 0 be the counting process for the number of failures observed in (0, t] for the /th individual in the ith group, / = 1 , . . , πιο; i — 0 , . . ,p. The corresponding at risk processes are Yn{t), and again we assume independent censoring.

26), however, takes the estimates as defined at all /, but constant following the maximum observed time. The former convention is more appropriate in most contexts, but the latter is convenient for some theoretical arguments. (u) = N(u) — N(u~). 5. {u) —» oo for all u € (0, fl as η —» oo, it is shown that A(r) ->A(f) and [Λ( )-Λ(/)]/ν(/) ^Λ'(0,1), α 5 ί where —» and —> indicate convergence in probability and convergence in distribution, respectively. 5, where items are placed on test in the ith group at time 0, and let Nu(t),t > 0 be the counting process for the number of failures observed in (0, t] for the /th individual in the ith group, / = 1 , .

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