Advantages of hierarchical linear modeling

Practical Assessment, Research and Evaluation

Volumn 7, Issue 1, 2001, Pages

  Osborne, Jason W ^a  

^a UNIVERSITY OF OKLAHOMA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 84893669814     PISSN: None     EISSN: 15317714     Source Type: Journal    
DOI: None     Document Type: Article

References (7)

1. Bryk, A.S., & Raudenbush, S. W. (1992). Hierarchical linear models: Applications and data analysis methods. Newbury Park, CA: Sage Publications.
2. Cohen, J., & Cohen, P. (1983). Applied multiple regression/correlation analysis for the behavioral sciences. Hillsdale, NJ: Lawrence Erlbaum Associates, Inc.
3. Draper, D. (1995). Inference and hierarchical modeling in the social sciences. Journal of Educational and Behavioral Statistics, 20 (2), 115-147.
4. Hoffman, D. A., & Gavin, M. B. (1998). Centering decisions in hierarchical linear models: Implications for research in organizations. Journal of Management, 24(5), 623-641.
5. Nezlek, J. B., & Zyzniewski, L. E. (1998). Using hierarchical linear modeling to analyze grouped data. Group Dynamics, 2, 313-320.
6. Pedhazur, E. J. (1997). Multiple regression in behavioral research, (pp. 675-711). Harcourt Brace: Orlando, FL.
7. Raudenbush, S. W. (1995). Reexamining, reaffirming, and improving application of hierarchical models. Journal of Educational and Behavioral Statistics, 20 (2), 210-220.