Survival Analysis

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Overview

Survival analysis is a class of statistical methods for studying the occurrence and timing of events. Statistical analysis of longitudinal data, particularly censored data, lies at the heart of social work research, and many of social work research's empirical problems, such as child welfare, welfare policy, evaluation of welfare-to-work programs, and mental health, can be formulated as investigations of timing of event occurrence. Social work researchers also often need to analyze multilevel or grouped data (for example, event times formed by sibling groups or mother-child dyads or recurrences of events such as reentries into foster care), but these and other more robust methods can be challenging to social work researchers without a background in higher math.

With clearly written summaries and plentiful examples, all written with social work issues and social work researchers in mind, this pocket guide will put this important statistical tool in the hands of many more social work researchers than have been able to use it before, to the field's benefit.

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Editorial Reviews

Doody's Review Service
Reviewer: Diane M Tomasic, EdD, RN (Slippery Rock University )
Description: Survival analysis is a collection of statistical methods to do with whether and when an event of interest takes place. This book, part of the Pocket Guides to Social Work Research Methods, describes the process of survival analysis research.
Purpose: The purpose is to make the statistical principles and application strategies more accessible to general researchers and to illustrate the application of survival analysis to social work research. This area of analysis is not included in many research books. The author has met these objectives.
Audience: Individuals conducting social work research are the target audience for this book. It may also be of interest to sociologists and engineering researchers who conduct similar research. The author has based this book on a five-year research study using survival analysis methodology and six years of teaching longitudinal methods.
Features: An introduction to survival analysis research begins the book, which provides examples of why and when survival analysis should be used. The second chapter discusses the key concepts related to survival analysis research and includes two descriptive methods and graphic approaches. Chapters 3 to 6 deal with the types of models available to this type of analysis. Chapter 7 covers the statistical packages available for survival analysis. The book concludes with a final chapter on some pitfalls of the research and directions for future research.
Assessment: This should be quite useful to researchers using longitudinal data to study the timing of events. This type of analysis is at the heart of social work research. If detailed methodology information is needed, readers are referred to a research/statistical methods book.
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Product Details

  • ISBN-13: 9780195337518
  • Publisher: Oxford University Press, USA
  • Publication date: 1/25/2010
  • Series: PKT GD TO SOCIAL WORK RESEARCH METHODS Series
  • Edition description: New Edition
  • Pages: 176
  • Product dimensions: 8.20 (w) x 5.50 (h) x 0.50 (d)

Meet the Author

Shenyang Guo, Ph.D., is Professor of Social Work at the University of North Carolina at Chapel Hill.

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Table of Contents

1. Introduction
2. Key Concepts and Descriptive Approaches
3. The Discrete-Time Models
4. The Cox Proportional Hazards Model
5. The Parametric Models
6. Multilevel Analysis of the Time-to-Event Data
7. Computing Software Packages for Survival Analysis
8. Concluding Remarks
Glossary
References
Index

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