Structural Equation Modeling (SEM) offers flexible statistical models for the social science researcher. A variety of software packages are available for implementing SEM with researchers’ datasets and are becoming increasingly sophisticated. This talk will briefly outline SEM in comparison with more familiar statistical models (such as linear regression) and review several R packages tailored for the SEM community. In addition, these packages are compared to perhaps the most well-known commercial package available, MPlus.

Justin Wild is a doctoral candidate at Indiana University studying Education Policy Studies, with a concentration in International and Comparative Education, and Inquiry Methodology. He has a Master’s of Arts in African Studies and a Master’s of Public Affairs from Indiana University. His research addresses K-12 language of instruction, language ecology, foreign language learning, evaluation in education, large-scale assessments, multi-method research, and cross-cultural issues. His geographic focus is Tanzania, East Africa.

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