Online texts and programs

• Visit Joop Hox's homepage from where you can view chapters of his Multilevel book. Download examples from his book at UCLA's Academic Technology Services or get the previous edition of his text (Hox, J. (1995). Applied Multilevel Analysis).
• A free electronic version of Multilevel Statistical Models (Goldstein, 1995), including recent corrections, is also available from the author's homepage.
• There is also a paper by Annie Qu of PRI, titled "Comparison of PROC MIXED in SAS and HLM for Hierarchical Linear Models" on the PSU website.
• Power analysis program by the HLM authors can be found at the W.T. Grant foundation website.
• The two-level power analysis program PINT is available from Tom Snijders' website.
• Don Hedeker’s MIXREG/MIXOR programs and documentation can be found at his Mixreg/Mixor homepage
• A number of papers is also available on Judith Singer's website:
• http://www.stanford.edu/class/educ260/sasprocmixed.pdf: Using SAS PROC MIXED to fit multilevel models, hierarchical models, and individual growth models. This is a reprint of a paper which appeared in the Journal of Educational and Behavioral Statistics in Winter 1998. It is written as a step-by-step tutorial that shows how to use SAS to fit the two most common multilevel models: (1) two-level models, designed for data on individuals nested within naturally occuring hierarchies (e.g., students within classes) and (2) individual growth models, designed for exploring longitudinal data (on individuals) over time. The conclusion provides code for three level models and an appendix provides code for working with multilevel data in SAS.
• http://gseweb.harvard.edu/~faculty/singer/Papers/devpsych.pdf: The design and analysis of longitudinal studies of development and psychopathology in context: Statistical models and methodological recommendations. . This is a reprint of a paper which appeared in Development and Psychopathology in 1998. The paper shows how researchers can use both individual growth modeling and the methods of survival analysis to explore development over time. In addition to presenting the fundamental statistical models, the paper presents recommendations for research design and measurement.
• http://gseweb.harvard.edu/~faculty/singer/Papers/ccare.pdf: Early child care selection: Variation by geographic location, maternal characteristics, and family structure. This is a reprint of of a paper which appeared in Developmental Psychology in 1998. Analyzing data from a national probability sample of children under 6, we use discrete-time survival analysis to examine the predictors of age at first placement into formal day care.
• More on the book by Singer & Willet can be found at: Applied Longitudinal Data Analysis: Modeling Change and Event Occurrence, New York: Oxford University Press, March, 2003
• An overview of multilevel modeling techniques and appropriate use can be found on Ita Kreft's homepage at http://www.calstatela.edu/faculty/ikreft. See http://www.calstatela.edu/faculty/ikreft/quarterly/quarterly.html
  for Are Multilevel Techniques Necessary? An overview, including Simulation Studies
• Hierarchical linear modeling at Wikipedia
  

Presentations and papers by HLM authors

Presentations:

• Raudenbush, S.W.  (2003).  “Designing Field Trials of Educational Innovations.”  Invited speaker at the DRDC Conference “Conceptualizing Scale-UP: Multidisciplinary Perspectives” Washington DC (Nov. 2003).
• Raudenbush, S.W.  (2002).  “Identifying Scientifically-Based Research in Education.”  Invited speaker at the Scientifically Based Research Seminar, U.S. Department of Education, Washington DC (Feb. 2002).
• Raudenbush, S.W.  (2002).  “New Directions in the Evaluation of Title I.”  Invited speaker at the Secretary’s Forum on Research and Value-Added Assessment Data, U.S. Department of Education, Washington DC (Dec. 2002).

Articles and chapters: (from 1996 to present).

To check for recent updates, please visit Steve Raudenbush's page 

• Raudenbush, S.W., Hong, G., and Rowan, B. (in press).  Studying the causal effects of instruction with application to primary-school mathematics.  To appear in Ross, J. M., Bohrnstedt, G.W. and Hemphill, F.C. (editors), Instructional and Performance Consequences of High Poverty Schooling.  National Council for Educational Statistics, Washington DC.
• Johnson, C and Raudenbush, S.W. (in press).  A repeated measures, multilevel Rasch model with application to self-reported criminal behavior.  To appear in Bergeman, C.S. & Boker, S.M. (eds.) Quantitative Methodology in Aging Research.  Proceedings from the Notre Dame Series on Quantitative Methodology: Quantitative Methodology in Aging Research.  Erlbaum Press.
• Raudenbush, S.W.  (2004). What are value-added models estimating and what does this imply for statistical practice?  Journal of Educational and Behavioral Statistics, 29(1), 121-129.
• Raudenbush, S.W. , Johnson, C. and Sampson, R. J. (2003).  A multivariate, multilevel Rasch model for self-reported criminal behavior.  Sociological Methodology, Vol. 33(1), 169-211.
• Raudenbush, S.W. & Liu, X.  (2001).  Effects of Study Duration, Frequency of Observation, and Sample Size on Power in Studies of Group Differences in Polynomial Change.  Psychological Methods, 6(4), 387.401.
• Cheong, Y.F. & Raudenbush, S.W. (2000). Measurement and structural models for children’s problem behaviors.  Psychological Methods, 5(4), 477-495.
• Kuo, M., Mohler, B., Raudenbush, S.W., & Earls, F.J. (2000). Assessing exposure too violence using multiple informants: Application of hierarchical linear model.  The Journal of Child Psychology and Psychiatry, 41, 1049-1056.
• Miyazaki, Y & Raudenbush, S.W. (2000). A test for linkage of multiple cohorts from an accelerated longitudinal design. Psychological Methods, 5(1), 44-63.
• Raudenbush, S.W. & Liu Xiaofeng. (2000). Statistical power and optimal design for multisite randomized trials. Psychological Methods, 5(3), 199-213.
• Raudenbush, S.W., & Sampson, R. (1999). Assessing direct and indirect effects in multilevel designs with latent variables. Sociological Methods & Research, 28(2),123-153.
• Raudenbush, S.W., & Sampson, R. (1999). Ecometrics: Toward a science of assessing ecological settings, with application to the systematic social observations of neighborhoods. Sociological Methodology, 29, 1-41.
• Raudenbush, S.W., Fotiu, R.P., & Cheong, Y.F. (1998). Inequality of access to educational resources: A national report card for eighth grade math. Educational Evaluation and Policy Analysis, 20(4), 253-268.
• Raudenbush, S.W., & Kasim, R. (1998). Cognitive skill and economic inequality: Findings from the National Adult Literacy Survey. Harvard Educational Review, 68(1), 33-79.
• Raudenbush, S.W. (1997). Statistical analysis and optimal design for cluster randomized trials. Psychological Methods, 2(2), 173-185.
• Sampson, R.J., Raudenbush, S.W., & Earls, F. (1997). Neighborhoods and violent crime: A multilevel study of collective efficacy. Science, 277, 918-924.
• Kalaian, H.A. & Raudenbush, S.W. (1996). A multivariate mixed linear model for meta-analysis. Psychological Methods, 1(3), 227-235.