
 Visit Joop Hox's homepage
from where you can view
chapter 2 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.
 Power analysis program by the HLM authors can be found
at the University
of Michigan website.
 The twolevel 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 stepbystep tutorial that shows how to use SAS to
fit the two most common multilevel models: (1) twolevel
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 discretetime 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
 Hierarchical
linear modeling at Wikipedia

Presentations:
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 primaryschool
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 selfreported 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 valueadded models estimating and what does this imply
for statistical practice? Journal of Educational
and Behavioral Statistics, 29(1), 121129.
 Raudenbush, S.W. , Johnson, C. and Sampson, R. J. (2003).
A multivariate, multilevel Rasch
model for selfreported criminal behavior. Sociological
Methodology, Vol. 33(1), 169211.
 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), 477495.
 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, 10491056.
 Miyazaki, Y & Raudenbush, S.W. (2000). A
test for linkage of multiple cohorts from an accelerated
longitudinal design. Psychological Methods, 5(1),
4463.
 Raudenbush, S.W. & Liu Xiaofeng. (2000). Statistical
power and optimal design for multisite randomized trials.
Psychological Methods, 5(3), 199213.
 Raudenbush, S.W., & Sampson, R. (1999). Assessing
direct and indirect effects in multilevel designs with latent
variables. Sociological Methods & Research, 28(2),123153.
 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, 141.
 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), 253268.
 Raudenbush, S.W., & Kasim, R. (1998). Cognitive
skill and economic inequality: Findings from the National
Adult Literacy Survey. Harvard Educational Review,
68(1), 3379.
 Raudenbush, S.W. (1997). Statistical
analysis and optimal design for cluster randomized trials.
Psychological Methods, 2(2), 173185.
 Sampson, R.J., Raudenbush, S.W., & Earls, F. (1997).
Neighborhoods and violent
crime: A multilevel study of collective efficacy.
Science, 277, 918924.
 Kalaian, H.A. & Raudenbush, S.W. (1996). A
multivariate mixed linear model for metaanalysis.
Psychological Methods, 1(3), 227235.
