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    Manuel pratique pour l'analyse statistique...

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    Collection: Méthodes et savoirs
    n°2, 1998, 400 pages
    Papier ISBN : 978-2-7332-6002-9

    Abstract

    Eva Lelièvre and Arnaud Bringé, respectively researcher and statistician at Ined present this practical guide to event history analysis using SAS®, TDA® and STATA®.
    However, rather than simply  assessing the performance of each application, this comparison aims to show potential users the basic programming required to run the same analysis using each of these applications. It explains the content and range of results obtained and compares the various graphs that can be output. The aim is to provide users with a guide that will help them choose the right software according to their constraints and objectives.
    As a result, our review focuses on the steps required to carry out the most basic analysis, as well as any intermediate steps, before going on to cover more sophisticated analyses.
    This guide offers a well documented and systematic approach to event history analysis.

    Contents

    • Preface. Daniel Courgeau
    • Introduction

    1. From longitudinal analysis to event history analysis

    2. A new paradigm

    3. Minimum data

    4. Formalization of the analysis

    7. Recap

    8. Objectives of this guide

    9. Notations used throughout this guide

    • Chapter 1. Comparison of software applications

    1. Software packages compared

    2. Commands described in this guide

    3. Data files

    • Chapter 2. Non-parametric analysis of a single event

    1. Introduction

    2. Instructions in SAS, TDA and STAT

    3. Kaplan-Meier method (product-limit estimate)

    4. Actuarial methode

    5. Handling mising values

    6. Comparing survival functiuns for diffrenet groupss

    7. Cumulative intensity curves H(t): the problem of competing risks

    • Chapter 3. Parametric analysis of a single event

    1. Theory

    2. Different types of distribution

    3. Analysis with the Weibull model4. Estimating a Weibull model.

    • Chapter 4. Semi-parametric analysis of a single event: Cox model

    1. Introduction

    2. Theory

    3. Checking the assumption that risks ara proportional

    4. SAS - using PROC PHREG

    5. TDA - Using Rate = 1

    6. STATA version 4.0

    7. STATA version 5.0

    Chapter 5. Output and graphs

    1. The two operatin modes availbale in SAS

    2. The three programming methods used in SAS

    3. TDA : Output and graphs for a non-parametric analyssi

    4. STATA

    Conclusion

    Appendix