Multilevel Latent Class Analysis as an Alternative Method for Program Evaluation: An Application of the Michigan 21st Century Community Learning Centers Grant Program

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Abstract

The method of evaluation assisting to choose the most effective programs can directly maximize the use of the funding. With the presence of multiple programs, the hierarchical structure of the data is commonly ignored due to the complexity of the method. In this paper, Vermunt’s multilevel latent class analysis (MLCA) model is proposed as an alternative method for program evaluation. Using the conventional aggregation method as the cross- validation and comparison method, the purpose of this study is to present the differences between these two methods and to demonstrate how MLCA can be utilized in program evaluation with the empirical data from Michigan 21st Century Community Learning Centers Grant Program.

Authors

• Chi Chang, Michigan State University

• Kimberly S. Maier, Michigan State University

• Richard T. Houang, Michigan State University

• Laurie Van Egeren, Michigan State University

• Heng-Chieh Wu, Michigan State University