Long, J. Scott
. 1997. Regression Models for Categorical and Limited Dependent Variables. Thousand Oaks, CA: Sage.
2.
Bryk, A.
and S. Raudenbush. 1988. “Toward a More Appropriate Conceptualization of Research on School Effects: A Three-Level Hierarchical Linear Model.”American Journal of Education97:65-108.
3.
Cook, R.
and S. Weisberg. 1982. Residuals and Influence in Regression. London: Chapman & Hall.
4.
Cox, D.1958. Planning of Experiments. New York: John Wiley.
5.
Dempster, A.
, N. Laird, and D. Rubin. 1977. “Maximum Likelihood From Incomplete Data via the EM Algorithm.”Journal of the Royal Statistical Society, Series B 39:1-8.
6.
Dempster, A.
, D. Rubin, & R. Tsutakawa. 1981. “Estimation in Covariance Components Models.”Journal of the American Statistical Association76:341-353.
7.
Goldstein, H.1995. Multilevel Statistical Models. 2d ed.New York: John Wiley.
8.
Heckman, J.1976. “The Common Structure of Statistical Models of Innovation, Sample Selection Bias and Limited Dependent Variables and a Single Estimator for Such Models.”Annals of Economic and Social Measurement5:475-492.
9.
Hedeker, D.
and R. Gibbons. 1994. “A Random-Effects Ordinal Regression Model for Multilevel Analysis.”Biometrics50:933-944.
10.
Horney, J.
, D. W. Osgood, and I. H. Marshall1995. “Criminal Careers in the Short Term: Intra-individual Variability in Crime and its Relation to Local Life Circumstances. American Sociological Review60: 655-673.
11.
Huttenlocher, J.
, W. Haight, A. Bryk, and M. Seltzer. 1991. “Early Vocabulary Growth: Relation to Language Input and Gender.”Developmental Psychology27:236-249.
12.
Lindley, D.
and A. Smith. 1972. “Bayes Estimates for the Linear Model.”Journal of the Royal Statistical Society, Series B 34:1-41.
13.
Little, R.1995. “Modeling the Drop-Out Mechanism in Repeated Measures Studies.”Journal of the American Statistical Association90:1112-1121.
14.
Little, R.
and D. Rubin. 1987. Statistical Analysis With Missing Data. New York: John Wiley.
15.
Longford, N.1987. “A Fast Scoring Algorithm for Maximum Likelihood Estimation in Unbalanced Models With Nested Random Effects.”Biometrika74:817-827.
16.
Longford, N.1993. Random Coefficient Models. Oxford, UK: Clarendon.
17.
Mason, W.
, G. Wong, and B. Entwisle. 1984. “Contextual Analysis Through the Multilevel Linear Model.” Pp. 72-103 in Sociological Methodology 1983-1984, edited by S. Leinhardt. San Francisco: Jossey-Bass.
18.
Raudenbush, S.1993. “A Crossed Random Effects Model for Unbalanced Data With Applications in Cross-Sectional and Longitudinal Research.”Journal of Educational Statistics18:321-349.
19.
Raudenbush, S. W.
and A. S. Bryk. 2002. Hierarchical Linear Models: Applications and Data Analysis Methods. 2d ed.Newbury Park, CA: Sage.
20.
Rosenberg, B.1973. “Linear Regression With Randomly Dispersed Parameters.”Biometrika1(60): 65-72.
21.
Sampson, R.
, S. Raudenbush, and T. Earls. 1997. “Neighborhoods and Violent Crime: A Multilevel Study of Collective Efficacy.”Science277:918-924.
Seltzer, M.1993. “Sensitivity Analysis for Fixed Effects in the Hierarchical Model: A Gibbs Sampling Approach.”Journal of Educational Statistics18:207-235.