Structural equation modeling (SEM) appears to be the fastest growing multivariate statistical method in the educational, social and behavioral sciences (Hershberger, 2003). SEM is also known as covariance structural analysis, covariance modeling, and causal modeling. SEM enables one to test complicated theoretical models that involve not only direct effects but also indirect effects. SEM also permits the inclusion of both observed and unobserved variables (e.g., factors).

The workshop will introduce structural equation modeling and reasons of its popularity. The workshop will help researchers 1) identify research questions in a SEM and 2) how to interpret a SEM. SEM is a family of techniques instead of a single method.

Some of the different SEM techniques that will be discussed include:
• Path analysis
• Confirmatory factor analysis
• SEM with latent variables
• Mediation
• Multi-sample SEM
• Mean and covariance structural analysis
• Longitudinal Models (Latent growth curve models)
The workshop will introduce various techniques of SEM and demonstration using computer software.

[Download PDF Version of Pre-Conference Workshop 1]

Many textbooks and journal articles have been devoted to qualitative methods but the actual doing of qualitative research remains an ‘untold story’ (Cheek, 2000). With their inherent flexibility, qualitative studies often present unforeseen challenges in design and implementation. This workshop will address the practical, methodological and ethical issues of doing qualitative research based upon the experiences of the presenters’ experiences in conducting a four-year NIMH-funded qualitative study. While attention is given to dealing with external funders and working as a team, most of the topics are applicable to studies conducted by a solo investigator (e.g., dissertation research).

Topics addressed in the workshop include:
• Deciding on each team member’s role, time and effort
• Fostering teamwork and ensuring adequate supervision
• Recruiting study participants; working with gatekeepers and study sites
• Monitoring budgets and allocating resources
• Retaining and keeping track of study participants
• Managing data and ensuring confidentiality
• Debriefing re: emotional and ethical issues
• Using and applying strategies for rigor
• Use(s) of qualitative data analysis software
• Writing progress and final reports
• Ending the study: notifying participants and sharing findings (and feelings)
• Publishing results from the study

As qualitative studies gain in popularity, their success depends upon a sound infrastructure. Fostering rigorous methods and confidence in findings depends upon mentoring and sharing information on what works.

[Download PDF version of Pre-Conference Workshop 2]

Geographic and Spatial Analysis in Social Work Research: Concepts and Tools
Presenters: Claudia Coulton, Professor, Mandel School of Applied Social Science, Case Western Reserve University, Bridget Freisthler, Assistant Professor, School of Social Welfare, University of California Los Angeles

Social work has long been interested in how context affects the wellbeing of individuals and groups. In particular, the places where people live, work, go to school and carry out their activities have been implicated as a potential source of disadvantage, especially for people of color and for low income individuals. Researchers who are interested in these issues need to be familiar with a variety of methods of spatial and geographic analysis so that they can correctly describe and model these place-based processes. The presenters will discuss: the conceptual basis for geographic and spatial analysis in social work research, sources of geographically referenced data and geo coding methods, the uses of maps for exploring spatial patterns in data, statistical approaches to contextual and spatial analysis (including multi-level modeling with geographic units, spatial dependence, spatial regression and spatial clustering methods).

[Download PDF version of Pre-Conference Worskhop 3]