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Titlebook: Analysis of Multivariate Survival Data; Philip Hougaard Book 2000 Springer-Verlag New York, Inc. 2000 Multivariate Survival Data.STATISTIC

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樓主: T-Lymphocyte
51#
發(fā)表于 2025-3-30 09:23:05 | 只看該作者
52#
發(fā)表于 2025-3-30 14:52:48 | 只看該作者
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發(fā)表于 2025-3-30 18:50:41 | 只看該作者
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發(fā)表于 2025-3-30 20:47:00 | 只看該作者
55#
發(fā)表于 2025-3-31 01:55:25 | 只看該作者
56#
發(fā)表于 2025-3-31 05:21:51 | 只看該作者
Statistical inference for shared frailty models,ocedures. Estimation difficulties have previously limited the applicability of the shared frailty models. There have, however, been a number of suggestions on how to estimate the parameters. Reasons for the many choices are, of course, that some formulas are complicated and that iteration can be tim
57#
發(fā)表于 2025-3-31 09:44:58 | 只看該作者
Multivariate frailty models,s. In particular, for truly multivariate data, that is, when there are three or more observations, we need more models with varying degrees of dependence. This general frailty approach can be used to create a random treatment by group interaction, or other models with several sources of variation. S
58#
發(fā)表于 2025-3-31 14:23:14 | 只看該作者
Instantaneous and short-term frailty models,ls studied until now lead to long-term dependence. Important examples are the Markov multi-state models and the shared frailty models. Only a single standard model, the Marshall-Olkin model of Section 5.5.4, displays instantaneous dependence. No standard models show short-term dependence, even thoug
59#
發(fā)表于 2025-3-31 21:23:46 | 只看該作者
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