Jason
Newsom's multilevel regression page also has examples
of various analyses, along with discusssion of specific
topics like centering and examination of the residual
files produced by HLM.

The UCLA
Academic Technology Services also provide useful links
to other multilevel texts such as "Introduction to
Multilevel Modeling" by Ita Kreft and Jan de Leeuw;
"Multilevel Analysis: An Introduction to Basic and
Advanced Multilevel Modeling" by Tom Snijders and
Roel Bosker; and "Multilevel Statistical Analysis"
by Harvey Goldstein. A video "Longitudinal
Research: Present Status and Future Prospects"
by Judith Singer & John Willett, which considers strategies
for improving the analysis of longitudinal data, is also
available here.

An overview of the logic and rationale of hierarchical
linear models - A Special Issue: Focus on Hierarchical
Linear Modeling. Journal of Management, November
1, 1997 by David A. Hofmann.

Interaction between individuals and situations: using
HLM procedures to estimate reciprocal relationships
- A Special Issue: Focus on Hierarchical Linear Modeling.
Journal of Management, November 1, 1997 by Mark
A. Griffin.

The application of HLM to the analysis of the dynamic
interaction of environment, person and behavior - hierarchical
linear modeling- A Special Issue: Focus on Hierarchical
Linear Modeling. Journal of Management, November
1, 1997 by Jeffrey B. Vancouver.

Bock, R. (1975). Multivariate Statistical Methods in
Behavioral Research. New York: McGrawHill.

Breslow, N., & Clayton, D. (1993). Approximate inference
in generalized linear mixed models. Journal of the American
Statistical Association, 88, 925.

Bryk, A., & Raudenbush, S. W. (1992). Hierarchical
Linear Models for Social and Behavioral Research: Applications
and Data Analysis Methods. Newbury Park, CA: Sage.

Cheong, Y. F., Fotiu, R. P., & Raudenbush, S. W. (2001).
Efficiency and robustness of alternative estimators for
2- and 3-level models: The case of NAEP. Journal
of Educational and Behavioral Statistics, 26,
411-429.

Dempster, A., Laird, N., & Rubin, D. (1977). Maximum
likelihood from incomplete data via the EM algorithm. Journal
of the Royal Statistical Society, Series B(39), 18.

Goldstein, H.I. (2003). Multilevel statistical models.(3rd
Edition). London: Edward Arnold.

Hox, J. (2002). Multilevel analysis: Techniques and
applications. Mahwah, NJ: Erlbaum.

Jennrich, R., & Schluchter, M. (1986). Unbalanced
repeated measures models with structured covariance matrices.
Biometrics, 42, 805-820.

Kreft, I., & de Leeuw, J. (1998). Introducing multilevel
modeling. London: Sage.

Longford, N. (1993). Random Coefficient Models.
Oxford: Clarendon Press.

McCullagh, P., & Nelder, J. (1989). Generalized
Linear Models, 2nd Edition. London: Chapman and Hill.

Pinheiro, J., & Bates, D. (1995). Approximations to
the log-likelihood function in the nonlinear mixed-effects
model. Journal of Computational and Graphical Statistics,
4, 12-35.

Raudenbush, S. (1993). A crossed random effects model
for unbalanced data with applications in cross-sectional
and longitudinal research. Journal of Educational Statistics,
18(4), 321-349.

Raudenbush, S. W., & Bryk, A. S. (2002). Hierarchical
Linear Models: Applications and Data Analysis Methods, Second
Edition. Newbury Park, CA: Sage.

Raudenbush, S. W., & Sampson, R. (1999). Assessing
direct and indirect associations in multilevel designs with
latent variables. Sociological Methods and Research,
28(2), 123-153.

Rodriguez, G., & Goldman, N. (1995). An assessment
of estimation procedures for multilevel models with binary
responses. Journal of the royal Statistical Society,
A, 158, 73-89.

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with random effects. Biometrika, 40, 719-727.

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analysis: An introduction to basic and advanced multilevel
modeling. London: Sage.

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of the nonlinear hierarchical model estimation via approximate
maximum likelihood. Unpublished apprenticeship paper, College
of Education, Michigan State University.

Yang, M.L. (1998). Increasing the efficiency in estimating
multilevel Bernoulli models [Diss], East Lansing, MI: Michigan
State University.

Bryk, A.S., & Raudenbush, S.W. (1987). Application
of hierarchical linear models to assessing change. Psychological
Bulletin, 101, 147-158.

Cudeck, R., Klebe, K.J. (2002). Multiphase mixed-effects
models for repeated measures data. Psychological Methods,
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Problem Youth: Delinquency, Substance Use, and Mental Health
Problems. New York: SpringerVerlag.

Huttenlocher, J.E., Haight, W., Bryk, A.S., & Seltzer,
M. (1991). Early vocabulary growth: Relations to language
input and gender. Developmental Psychology, 22(2),
236-249.

Miyazaki, Y., & Raudenbush, S.W. (2000). A test for
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design. Psychological Methods, 5, 44-63.

Raudenbush, S. W. (2001). Toward a coherent framework
for comparing trajectories of individual change. Collins,
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Change (pp. 33-64). Washington, DC: The
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Raudenbush, S. W., & Chan, W.S. (1993). Application
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Raudenbush, S. W., Yang, M.l., & Yosef, M. (2000).
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Singer, J.D., & Willett, J.B. (2003). Applied Longitudinal
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London: Sage.

Pinheiro, J., & Bates, D. (1995). Approximations to
the log-likelihood function in the nonlinear mixed-effects
model. Journal of Computational and Graphical Statistics,
4, 12-35.

Raudenbush, S. W., & Bhumirat, C. (1992). The distribution
of resources for primary education and its consequences
for educational achievement in Thailand. International
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Rodriquez, G., & Goldman, N. (1995). An assessment
of estimation procedures for multilevel models with binary
responses. Journal of the Royal Statistical Society,
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Rowan, B., Raudenbush, S., & Cheong, Y. (1993). Teaching
as a nonroutine task: Implications for the organizational
design of schools. Educational Administration Quarterly,
29(4), 479-500.

Rowan, R., Raudenbush, & Kang, S. (1991). Organizational
design in high schools: A multilevel analysis. American
Journal of Education, 99(2), 238-266.

Snijders, T.A.B., & Bosker, R.J. (1999). Multilevel
analysis: An introduction to basic and advanced multilevel
modeling. London: Sage.

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Wong, G., & Mason, W. (1985). The hierarchical logistic
regression model for multilevel analysis. Journal of
the American Statistical Association, 80(391),
513-524.

Garner, C., & Raudenbush, S. (1991). Neighborhood
effects on educational attainment: A multi-level analysis
of the influence of pupil ability, family, school, and neighborhood.
Sociology of Education, 64(4), 251-262.

Hill, P.W., & Goldstein, H. (1998). Multilevel modeling
of educational data with cross-classification and missing
identification of units. Journal of Educational and Behavioral
Statistics, 23, 117-128.

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with missing data. New York: Wiley.

Little, R., & Schenker, N. (1995). Missing data. In
G. Arminger, C. C. Clogg & M. E. Sobel (Eds.), Handbook
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Service.

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in Surveys. New York: Wiley.

Schafer, J. (1997). Analysis of Incomplete Multivariate
Data. London: Chapman & Hall.

Pfefferman, D., Skinner, C.J., Homes, D.J., Goldstein,
H., and Rasbash, J. (1998). Weighting for unequal selection
models in multilevel models. Journal of the Royal Statistical
Society, Series B, 60, 1, 23-40.

Raudenbush, S. W., & Sampson, R. (1999). Assessing
direct and indirect associations in multilevel designs with
latent variables. Sociological Methods and Research,
28(2), 123-153.

Bauer, D. J., & Curran, P. J. (in press). Probing
interactions in fixed and multilevel regression: Inferential
and graphical techniques. Multivariate Behavioral Research.

Curran, P. J., Bauer, D. J, & Willoughby, M. T. (in
press). Testing and probing interactions in hierarchical
linear growth models. To appear in C. S. Bergeman &
S. M. Boker (Eds.), The Notre Dame Series on Quantitative
Methodology, Volume 1: Methodological Issues in Aging Research.
Mahwah, NJ: Lawrence Erlbaum Associates.

Krull, J. L., & MacKinnon, D. P. (2001). Multilevel
modeling of individual and group level mediated effects.
Multivariate Behavioral Research, 36, 249-277.

Kenny, D.A., Korchmaros, J.D., & Bolger, N. (2003).
Lower level mediation in multilevel models. Psychological
Methods, 8, 115-128.

Pituch, K. A., Whittaker, T. A., & Stapleton, L. M.
(2005). A Comparison of Methods to Test for Mediation in
Multisite Experiments. Multivariate Behavioral Research,
40, 1-23.

Pituch, K. A., Stapleton, L. M., & Kang, J. Y. (2006).A comparison of single sample and bootstrap methods to assess mediation in cluster randomized trials. Multivariate Behavioral Research, 41, 367-400.

Raudenbush, S.W., & Bryk, A.S. (2002). Hierarchical
Linear Models: Applications and data analysis methods
(2nd Edition). Thousand Oaks, CA: Sage.

Tate, R. L., & Pituch, K. A. (2007). Multivariate hierarchical linear modeling in randomized field experiments. Journal of Experimental Education, 75, 317-337.

Thum, Y.M. (1997). Hierarchical linear models for multivariate
outcomes. Journal of Educational and Behavioral Statistics,
22, 77-108.

Kreft, I.G.G., de Leeuw, J., & Aiken, L. (1995).
The effect of different forms of centering in hierarchical
linear models. Multivariate Behavioral Research,
30, 1-22.

Kreft, I.G.G. (1997). The interactive effect of alcohol
prevention programs in high school classes: An illustration
of item homogeneity scaling and multilevel analysis techniques.
In K.J. Bryant, M. Windle, and S.G. West (eds.), Science
of prevention: Methodological advances from alcohol and
substance abuse research. Washington, D.C.: American
Psychological Association.

Ecob, R., & Der, G. (2003). An interative method for
the detection of outliers in longitudinal growth data using
multilevel models. In S.P. Reise & N. Duan (Eds.), Multilevel
modeling: Methodological advances, issues, and applications
(pp. 229-254). Mahwah, NJ: Erlbaum.

Langford, I.H., & Lewis, T. (1998). Outliers in multilevel
data. Journal of the Royal Statistical Society, Series
A, 161,121-160.

Seltzer, M., Novak, J., Choi, K., & Lim, N. (2002).
Sensitivity analysis form hierarchical models employing
t level-1 assumptions. Journal of Educational & Behavioral
Statistics, 27, 181-222.

Barnett, R. C., Brennan, R. T., Raudenbush, S. W., &
Marshall, N. L. (1993). Gender and the relationship between
marital role equality and psychological distress: A study
of dual earner couples. Journal of Personality and Social
Psychology, 64, 794-806.

Raudenbush, S.W., & Willms, J.D. (l991). Pupils,
Classrooms. and Schools: International Studies of Schooling
from a Multilevel Perspective. New York: Academic
Press.

Raudenbush, S.W. (in press). Many small groups.
To appear in, deLeeuw, Jan and Kreft, Ita (Eds.),
Handbook of Quantitative Multilevel Analysis. Kluwer
Press.

Raudenbush, S. W. (1999). Hierarchical models. In S. Kotz
(Ed.), Encyclopedia of Statistical Sciences, Update
Volume 3 (pp. 318-323). New York: John Wiley &
Sons, Inc.

Raudenbush, S.W. (1993). Hierarchical linear models and
experimental design. In Lynne K. Edwards (Ed.), Applied
analysis of variance in behavioral science. New York:
Marcel Dekker.

Harrison, D. and Raudenbush, S.W. (in press).
Linear regression and hierarchical linear models. To appear
in Green, J., Camilli, G., and Elmore, P. (editors) Complementary
Methods for Research in Education. Washington,
DC: American Educational Research Association.

Sampson, R.J., Morenoff, J.D. and Raudenbush, S.W.
(in press). Social anatomy of racial and ethnic disparities
in violence. To appear in American Journal of Public
Health.

Sampson, R.J. & Raudenbush, S.W.(in press). The social
structure of seeing disorder. To appear in Social
Psychology Quarterly.

Bingenheimer, J., Leventhal, T., Brooks-Gunn, J. and Raudenbush,
S.W. (in press). Measurement equivalence for
two dimensions of children’s home environments.
To appear in Journal of Family Psychology.

Bingenheimer, J. & Raudenbush, S.W. (2004). Statistical
and substantive inferences in public health: Issues in the
application of multilevel models. Annual Review of Public
Health, 25, 53-77.

Kang, S.J., Rowan, B., and Raudenbush, S.W. (2004).
Estimating the effects of academic departments on organic
design in high schools: A crossed-multilevel analysis.
In Hoy, W.K. and Miskel, C. (eds.) Educational Administration,
Policy, and Reform: Research and Measurement,
(pp.123-152), Information Age Publishing.

Ewing, R., Schmid, T.L., Killingsworth, R.E., Zlot, A.I.
and Raudenbush, S.W. (2003). Relationship between urban
sprawl and physical activity, obesity, and morbidity. The
American Journal of Health Promotion,18(1),
47-57.

Buka, S. L., Brennan, R.T., Rich-Edwards, J.W., Raudenbush,
S.W. and Earls, F. (2003). Neighborhood support and the
birth weight of urban infants. The American Journal of
Epidemiology, 157(1), 1-8.

Cohen, D.K., Raudenbush, S.W., & Ball, D.L. (2003).
Resources, instruction, and research. Educational Evaluation
and Policy Analysis, 25(2), 1-24.

Raudenbush, S.W. (2003). The quantitative assessment
of neighborhood social environment. In Kawachi, I
and Berkman, L. (Eds.), Neighborhoods and Health
(pp. 112-131). Oxford University Press.

Raudenbush, S.W. (2003). [Comments on Measurement,
Objectivity, and Trust by Theodore M. Porter.] Measurement,
1(4), 274-278.

Cohen, D., K., Raudenbush, S. W., & Ball, D. L. (2002).
Resources, Instruction, and Research. In F.
Mosteller & R. Boruch (Eds.), Evidence matters: Randomized
trials in education research, (pp. 80-119). Washington,
DC: Brookings Institution Press.

Raudenbush, S.W. (2002). Alternative Covariance Structures
for Polynomial Models of Individual Growth and Change.
In Moskowitz/Hershberger(Eds.), Modeling Intraindividual
variability with repeated measures data: Methods and Applications
(pp. 25-58). Mahway, New Jersey: Lawrence Erlbaum
Associates.

Raudenbush, S.W. (2002). Mixed modeling matures [Review
of the books "Linear mixed models for longitudinal
data" (and) "Mixed-effects models in S and S-Plus],
by G. Verbeke, & G. Molenberghs (and) J. Pinheiro, &
D. Bates (New York: Springer, 2000). Sociological Methods
and Research, 31(1), 110-118.

Raudenbush, S. W., & Kim, J.S. (2002). Statistical
issues in analysis of international comparisons of educational
achievement. In A. C. Porter & A. Gamoran (Eds.), Methodological
Advances in CrossNational Surveys of Educational Achievement
(pp. 267-294). Washington DC: National Academy Press.

Cheong, Y.F., Fotiu, R.P, & Raudenbush, S.W. (2001).
Efficiency and robustness of alternative estimators for
2- and 3- level models: The case of NAEP. To appear in Journal
of Educational & Behavioral Statistics.

Duncan, G.J. & Raudenbush, S.W. (2001). Neighborhoods
and adolescent development: How can we determine the links?
In Alan Booth and Nan Crouter (Eds.), Does it Take a
Village? Community Effects on Children, Adolescents, and
Families, [pp. 105-136]. State College, PA: Pennsylvania
State University Press.

Duncan, G.J. & Raudenbush, S.W. (2001). Getting context
right in quantitative studies of child development.
In Arland Thornton (Ed.), The Well-Being of Children
and Families, [pp.356-383]. Ann Arbor, MI: The University
of Michigan Press.

Kerckhoff, A.C., Raudenbush, S.W. & Glennie, E. (2001).
Education, cognitive skill, and labor force outcomes. Sociology
of Education, 74(1), 1-24.

Morenoff, J.D., Sampson, R.J. and Raudenbush, S.W. (2001).
Neighborhood structure, social processes, and the spatial
dynamics of urban violence. Criminology, 39(37),
517-560.

Raudenbush, S.W. (2001). Comparing personal trajectories
and drawing causal inferences from longitudinal data. Annual
Review of Psychology, 52, 501-525.

Sampson, R.J. & Raudenbush, S.W. (Feb. 2001). Disorder
in urban neighborhoods – Does it lead to crime? National
Institute of Justice, Research Brief.

Raudenbush, S.W. (2001). Toward a coherent framework for
comparing trajectories of individual change. Collins, L.
and Sayer, A. (Eds.), New Methods for the Analysis of
Change (pp.35-64). Washington D.C.: The American Psychological
Association.

Raudenbush, S.W. (2000). Synthesizing Results for NAEP
Trial State Assessment. In Grissmer, D.W. and Ross, Michael
(Ed.), Analytic Issues in the Assessment of Student Achievement,
Washington, DC: National center for Educational Statistics.

Raudenbush, S.W., Yang, Meng-Li & Yosef, M. (2000).
Maximum likelihood for generalized linear models with nested
random effects via high-order, multivariate Laplace approximation.
Journal of Computational and Graphical Statistics,
9(1), 141-157.

Raudenbush, S.W. (1999). Hierarchical models.In S. Kotz,
(Ed.), Encyclopedia of Statistical Sciences, Update
Volume 3, (pp. 318-323). New York: John Wiley.

Raudenbush, S.W., Fotiu, R.P. & Cheong, Y.F. (1999).
Synthesizing results from trial state assesment. Journal
of Educational and Behavioral Statistics, 24(4),
413-438.

Sampson, R.J. & Raudenbush, S.W. (1999). Systematic
social observation of public spaces: A new look at disorder
in urban neighborhoods. American Journal of Sociology,
105(3), 603-651.

Duncan, G.J., & Raudenbush, S.W. (1998). Assessing
the effects of context in studies of child and youth development.
Educational Psychologist, 34(1), 29-41.

Kasim, R. & Raudenbush, S. (1998). Application of
Gibbs sampling to nested variance components models with
heterogenous with-in group variance. Journal of Educational
and Behavioral Statistics, 23(2), 93-116.

Raudenbush S.W. (1998, May). [Review of the book A
solution to the ecological inference problem: Reconstructing
individual behavior from aggregate data by Gary King.]
American Journal of Sociology, 103(6), 1770-1772.

Sampson, R.J., Raudenbush, S.W., & Earls, F. (1998,
April). Neighborhood collective Efficacy - does it help
reduce violence? National Institute of Justice Research
Preview, Washington, DC. Abstracted with permission
from Sampson, R.J., Raudenbush, S.W. & Earls, F. “Neighborhoods
& violent crime - A multilevel study of collective efficacy”,
Science, 277, (1-7).

Selner-O'Hagan, M.B., Kindlon, D.J., Buka, S.L., Raudenbush,
S.W., & Earls, F.J. (1998). Assessing Exposure to Violence
in Urban Youth. Journal of Child Psychology and Psychiatry
and Allied Disciplines, 39(2), 215-224.

Willms, J.D., & Raudenbush, S. (1997). Effective
schools research: Methodological issues. In Saha,, L.J.
(Ed.), The International Encyclopaedia of the Sociology
of Education (1934-1939). New York: Elsevier.

Kindlon, D.J., Wright, B.D., Raudenbush, S.W. & Earls,
F. (1996). The measurement of children's exposure to violence:
A Rasch analysis. International Journal of Methods in
Psychiatric Research, 6, 187-194.

Raudenbush, S.W., Cheong, Y.F., Fotiu, R.P. (1996). Section
A, Social inequality, social segregation, and their relationship
to reading literacy in 22 countries. In M. Binkley, K. Rust,
and T. Williams (Eds.) The IEA Reading Literacy Study:
The United States in International Perspective, (pp.
5-62), Washington: National Center for Educational Statistics.

Raudenbush, S.W., Fotiu, R.P, Cheong, Y.F., & Ziazi,
Z.M. (1996). Synthesizing results from the Trial State Assessment.
American Statistical Association 1995 Proceedings of
the Section on Survey Research Methods, 1, 257-262.