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生存分析+R代码 利于自学

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  • TA的每日心情
    开心
    2015-2-17 10:44
  • 签到天数: 1 天

    [LV.1]初来乍到

    发表于 2015-10-18 23:15:10 | 显示全部楼层 |阅读模式
    This is the second edition of this text on survival analysis,
    originally published in 1996. As in the first edition, each chapter
    contains a presentation of its topic in “lecture-book” format
    together with objectives, an outline, key formulae, practice
    exercises, and a test. The “lecture-book” format has a
    sequence of illustrations and formulae in the left column of
    each page and a script in the right column. This format allows
    you to read the script in conjunction with the illustrations and
    formulae that high-light the main points, formulae, or examples
    being presented.
    This second edition has expanded the first edition by adding
    three new chapters and a revised computer appendix. The
    three new chapters are:
    Chapter 7. Parametric Survival Models
    Chapter 8. Recurrent Event Survival Analysis
    Chapter 9. Competing Risks Survival Analysis
    Chapter 7 extends survival analysis methods to a class of survival
    models, called parametric models, in which the distribution
    of the outcome (i.e., the time to event) is specified in
    terms of unknown parameters. Many such parametric models
    are acceleration failure time models, which provide an alternative
    measure to the hazard ratio called the “acceleration
    factor”. The general form of the likelihood for a parametric
    model that allows for left, right, or interval censored data is
    also described. The chapter concludes with an introduction
    to frailty models.
    Chapter 8 considers survival events that may occur more than
    once over the follow-up time for a given subject. Such events
    are called “recurrent events”. Analysis of such data can be
    carried out using a Cox PH model with the data layout augmented
    so that each subject has a line of data for each recurrent
    event. A variation of this approach uses a stratified
    Cox PH model, which stratifies on the order in which recurrent
    events occur. The use of “robust variance estimates” are
    recommended to adjust the variances of estimated model coefficients
    for correlation among recurrent events on the same
    subject.
    viii Preface
    Chapter 9 considers survival data in which each subject can
    experience only one of several different types of events (“competing
    risks”) over follow-up. Modeling such data can be carried
    out using a Cox model, a parametric survival model or a
    model which uses cumulative incidence (rather than survival).
    The Computer Appendix in the first edition of this text has
    now been revised and extended to provide step-by-step instructions
    for using the computer packages STATA (version
    7.0), SAS (version 8.2), and SPSS (version 11.5) to carry out
    the survival analyses presented in the main text. These computer
    packages are described in separate self-contained sections
    of the Computer Appendix, with the analysis of the same
    datasets illustrated in each section. The SPIDA package used
    in the first edition is no longer active and has therefore been
    omitted from the appendix and computer output in the main
    text.
    In addition to the above new material, the original six chapters
    have been modified slightly to correct for errata in the first
    edition, to clarify certain issues, and to add theoretical background,
    particularly regarding the formulation of the (partial)
    likelihood functions for the Cox PH (Chapter 3) and extended
    Cox (Chapter 6) models.
    The authors’ website for this textbook has the following weblink:
    http://www.sph.emory.edu/∼dkleinb/surv2.htm
    This website includes information on how to order this
    second edition from the publisher and a freely downloadable
    zip-file containing data-files for examples used in the textbook.
    Suggestions
    for Use
    This text was originally intended for self-study, but in the nine
    years since the first edition was published, it has also been effectively
    used as a text in a standard lecture-type classroom
    format. The text may also be use to supplement material covered
    in a course or to review previously learned material in
    a self-instructional course or self-planned learning activity.
    A more individualized learning program may be particularly
    suitable to a working professional who does not have the time
    to participate in a regularly scheduled course.
    Preface ix
    In working with any chapter, the learner is encouraged first to
    read the abbreviated outline and the objectives and then work
    through the presentation. The reader is then encouraged to
    read the detailed outline for a summary of the presentation,
    work through the practice exercises, and, finally, complete the
    test to check what has been learned.
    Recommended
    Preparation
    The ideal preparation for this text on survival analysis is a
    course on quantitative methods in epidemiology and a course
    in applied multiple regression. Also, knowledge of logistic regression,
    modeling strategies, and maximum likelihood techniques
    is crucial for the material on the Cox and parametric
    models described in chapters 3–9.
    Recommended references on these subjects, with suggested
    chapter readings are:
    Kleinbaum D, Kupper L, Muller K, and Nizam A, Applied
    Regression Analysis and Other Multivariable Methods,
    Third Edition, Duxbury Press, Pacific Grove, 1998, Chapters
    1–16, 22–23
    Kleinbaum D, Kupper L and Morgenstern H, Epidemiologic
    Research: Principles and Quantitative Methods, John
    Wiley and Sons, Publishers, New York, 1982, Chapters 20–
    24.
    Kleinbaum D and Klein M, Logistic Regression: A Self-
    Learning Text, Second Edition, Springer-Verlag Publishers,
    New York, Chapters 4–7, 11.
    Kleinbaum D, ActivEpi-A CD Rom Electronic Textbook on
    Fundamentals of Epidemiology, Springer-Verlag Publishers,
    New York, 2002, Chapters 13–15.
    A first course on the principles of epidemiologic research
    would be helpful, since all chapters in this text are written
    from the perspective of epidemiologic research. In particular,
    the reader should be familiar with the basic characteristics of
    epidemiologic study designs, and should have some idea of
    the frequently encountered problem of controlling for confounding
    and assessing interaction/effect modification. The
    above reference, ActivEpi, provides a convenient and hopefully
    enjoyable way to review epidemiology.
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    发表于 2016-1-7 21:13:18 | 显示全部楼层
    不错,很 这是精华
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    发表于 2016-1-7 21:14:21 | 显示全部楼层
    不错,很 这是精华,自学很有用的哦
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  • TA的每日心情
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    2017-12-15 11:07
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    [LV.7]常住居民III

    发表于 2016-3-13 11:58:36 | 显示全部楼层
    谢谢楼主无私分享!!
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  • TA的每日心情
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    2017-8-28 12:11
  • 签到天数: 12 天

    [LV.3]偶尔看看II

    发表于 2016-7-2 10:30:16 | 显示全部楼层
    感谢分享楼主好人
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    该用户从未签到

    发表于 2016-8-26 00:18:54 | 显示全部楼层
    感谢                                
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  • TA的每日心情
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    2016-11-18 09:14
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    [LV.2]偶尔看看I

    发表于 2016-11-18 09:19:32 | 显示全部楼层
    谢谢谢谢谢谢嘻嘻嘻嘻嘻
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  • TA的每日心情
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    8 小时前
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    [LV.10]以坛为家III

    发表于 2017-2-3 20:42:41 | 显示全部楼层
    感谢楼主辛苦分享!!
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