Social work researchers often conduct research with groups that are diverse in terms of gender, sexual orientation, race or ethnic background, or age. Consequently, social work researchers must take great care to establish research-design equivalence at all phases of the research process (e.g., problem formulation, research design, sampling, measurement selection, data collection, and data analysis); otherwise, the results might reflect methodological flaws rather
than true group differences and therefore lead to erroneous conclusions. This book introduces the methodological precautions that must be taken into consideration when conducting research with diverse groups. Multigroup Confirmatory Analysis (MG-CFA) using structural equation modeling (SEM) was
utilized to demonstrate how to assess seven types of measurement and structural equivalence that Milfont and Fischer (2010) have deemed important for studies with diverse samples. A hypothetical example was provided to illustrate how to design a study with good research-design equivalence. A case example was provided to demonstrate how to conduct an MG-CFA for each type of measurement and structural equivalence discussed. The Mplus syntax used to conduct the MG-CFA was provided. The
results from the MG-CFA analyses were written up as they would be for publication.
Dr. Antoinette Y. Farmer is associate professor and associate dean for academic affairs at Rutgers University's School of Social Work. Her research focuses on examining the social and interpersonal factors that affect parenting as well as how parenting practices influence adolescent high risk behaviors, such as delinquency and substance use. She co-edited a special issue of the Journal of Social Service Research, which was devoted to informing researchers of the methodological issues confronting them when conducting research with minority and oppressed populations. She has also written several chapters on this issue as well, with the most recent appearing in the Handbook of Social Work Research Methods (2nd Edition).
Chapter 1 Introduction ; Diversity: Its implications for Establishing Equivalence ; Sampling ; The Need to Consider Contextual Factors when Establishing Equivalence ; Organization of the Book ; Significance for Social Work ; Chapter 2 Research-Design Equivalence ; Overview ; Problem Formulation ; Research Design ; Sampling Equivalence ; Measurement Selection ; Data Collection ; Data Analysis ; Summary and Conclusion ; Chapter 3 Multigroup Confirmatory Factor Analysis to Establish Measurement and Structural Equivalence ; Overview ; Measurement Equivalence Defined ; Overview of Multigroup Confirmatory Factor Analysis ; Testing Measurement Equivalence Across Groups ; Distributional Analysis ; Baseline Measurement Models ; Multigroup Confirmatory Factor Analysis ; Advances in multigroup analysis ; Summary and Conclusion ; Chapter 4 Hypothetical Case Illustration ; Overview ; Hypothetical Case Illustration ; Summary and Conclusion ; Chapter 5 Conclusion ; Qualitative Methods in Establishing Measurement Equivalence ; The Challenge of Conducting Research to Establish Equivalence Using National Datasets ; Future Directions ; Social Work Doctoral Education ; References ; Appendix A Establishing the Base CFA Model Hispanic and African American Males ; Appendix B Adjusted Chi-Square Difference Test: Configural Versus Weak Factor Equivalent model ; Appendix C Measure equivalence using alternative SEM programs ; Index