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.
Author(s): Shenyang Guo
Publisher: Oxford University Press, USA
Year: 2010
Language: English
Pages: 176
Contents......Page 8
1. Introduction......Page 12
2. Key Concepts and Descriptive Approaches......Page 35
3. The Discrete-Time Models......Page 65
4. The Cox Proportional Hazards Model......Page 82
5. The Parametric Models......Page 107
6. Multilevel Analysis of Time-to-Event Data......Page 125
7. Computing Software Packages for Survival Analysis......Page 138
8. Concluding Remarks......Page 142
B......Page 148
D......Page 149
K......Page 150
M......Page 151
O......Page 152
P......Page 153
U......Page 154
Notes......Page 156
References......Page 158
C......Page 164
D......Page 165
G......Page 166
L......Page 167
N......Page 168
P......Page 169
S......Page 170
V......Page 171
W......Page 172