This course covers research methods for assessing the nature and extent of needs for social intervention, evaluating the success or failure of existing social welfare policies, and determining the anticipated consequences of alternative policies and interventions. Also considered will be values and assumptions underlying policies and research, similarities and differences between methods for developing social policy knowledge and those for basic knowledge development, strategies to promote utilization and dissemination of research results, and methods of studying community, regional, national, and comparative international policies.
The focus of the course this term will be on techniques to draw policy relevant inferences from data sets such as surveys. The course will review the fundamentals of regression analysis, bivariate and multivariate. Then we will focus on statistical inference using data sets with multicolinearity of variables in situations where theory provides only minimal guidance of how to deal with that. The emphasis will be on clarity of basic concepts, intuitive understanding of techniques, and explaining regression results, both coefficients and statistical tests, to non-technical policy decision makers. The course will also deal with power and limits of benefit cost analysis and related economic methods of policy analysis.
Multilevel models have become a standard statistical tool for quantitative research on neighborhoods, communities and schools. Interestingly, the multilevel model for cross-sectional data can easily accommodate longitudinal data where study participants are observed repeatedly. While this is sometimes not recognized, multilevel models for longitudinal data are closely related to other important longitudinal data models, such as fixed effects regression, an important technique for controlling for unobserved variables. This course focuses on the use of multilevel and longitudinal data analysis for social work research. The models discussed in this course are primarily intended, and best developed, for continuous outcomes, so are most appropriate for students with research questions that can in some way be conceptualized as continuous outcomes. The course is intended for students who have some familiarity with ordinary least squares regression, since the OLS model will be used as a starting point for discussion. The treatment of these topics involves some discussion of the underlying statistical theory, but is much more focused on the application of these models with real data. STATA is intended to be the primary statistical software used in this course.
Other SW832 Offerings
The course listings below are provided for reference only. These offerings may be subject to changed of cancellation.
No other course offerings found this term.