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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.
Structural Equation Modeling (SEM) has long been used in social
work research, but the writing on the topic is typically fragmented
and highly technical. This pocket guide fills a major gap in the
literature by providing social work researchers and doctoral
students with an accessible synthesis. The authors demonstrate two
SEM programs with distinct user interfaces and capabilities (Amos
and Mplus) with enough specificity that readers can conduct their
own analyses without consulting additional resources. Examples from
social work literature highlight best practices for the
specification, estimation, interpretation, and modification of
structural equation models. Unlike most sources on SEM, this book
provides clear guidelines on how to evaluate SEM output and how to
proceed when model fit is not acceptable.
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