Survival Analysis [Paperback]

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.

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

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. --Doody's

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