Hierarchical Linear Modeling
Associate Professor, Texas A&M University
|Course Time:||May 21-23 [5/21 (1:30 to 4:30 pm); 5/22-5/23 (9:00 to 12:00 pm and 1:30 to 4:30 pm)]|
|Course Location:||Harrington Education Center Tower (HECC), Room 632|
This course will provide you with an introduction to the theory and application of hierarchical linear models. Most data in the behavioral sciences has a multilevel structure, such as students nested within classrooms, patients nested within hospitals, participants nested within group treatment conditions and repeated measures nested within individuals. The major goals of this course are to understand the concepts related to hierarchical linear models, to specify your own models and analyze the data using one of the HLM programs, and to interpret the statistical findings to lay persons. This course will use the HLM software program including HLM and SPSS MIXED to perform the statistical analyses.
Hox, J. (2010). Multilevel analysis: Techniques and applications, Second Edition Florence, KY: Routledge (Taylor & France Group).
Raudenbush, S. W., & Bryk, A. S. (2002). Hierarchial linear models: Applications and data analysis methods (2nd Ed.) Thousands Oaks, CA: Sage.
Luke, D. (2004). Multilevel modeling. Thousands Oaks, CA: Sage.
Snijdres, T. A., & Bosker, R. J. (1999). Multilevel analysis: An introduction to basic and advanced multilevel modeling. Thousands Oaks, CA: Sage.
Bickel, R. (2007). Multilevel analysis for applied research: It's just regression!. New York, NY: Guilford.
O'Connell, A. A., & McCoach, D. B. (2008). Multilevel modeling of educational data. Charlotte, NC: Information Age Publishing.
Software:Two software packages will be used in this workshop, HLM 7.0 and Mplus 6.12. Demonstrations will be based on the student versions of the software. Student versions of the software can be downloaded for free by clicking the links below and following the instructions.