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E-raamat: Survival Analysis

(Professor of Social Work, University of North Carolina at Chapel Hill, Chapel Hill, NC)
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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 3
2. Key Concepts and Descriptive Approaches 26
3. The Discrete-Time Models 56
4. The Cox Proportional Hazards Model 73
5. The Parametric Models 98
6. Multilevel Analysis of Time-to-Event Data 116
7. Computing Software Packages for Survival Analysis 129
8. Concluding Remarks 133
Glossary 139
Notes 147
References 149
Index 155
Shenyang Guo, Ph.D., is Professor of Social Work at the University of North Carolina at Chapel Hill.