Journal ArticleDOI
Multilevel mixed linear model analysis using iterative generalized least squares
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In this paper, an iterative generalized least squares estimation procedure is given and shown to be equivalent to maximum likelihood in the normal case, and applications to complex surveys, longitudinal data, and estimation in multivariate models with missing responses are discussed.Abstract:
SUMMARY Models for the analysis of hierarchically structured data are discussed. An iterative generalized least squares estimation procedure is given and shown to be equivalent to maximum likelihood in the normal case. There is a discussion of applications to complex surveys, longitudinal data, and estimation in multivariate models with missing responses. An example is given using educational data.read more
Citations
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Book
Multilevel Statistical Models
TL;DR: In this article, the authors present a general classification notation for multilevel models and a discussion of the general structure and maximum likelihood estimation for a multi-level model, as well as the adequacy of Ordinary Least Squares estimates.
Journal ArticleDOI
Approximate inference in generalized linear mixed models
Norman E. Breslow,D. G. Clayton +1 more
TL;DR: In this paper, generalized linear mixed models (GLMM) are used to estimate the marginal quasi-likelihood for the mean parameters and the conditional variance for the variances, and the dispersion matrix is specified in terms of a rank deficient inverse covariance matrix.
Journal ArticleDOI
Modeling Multilevel Data Structures
TL;DR: The logic and statistical theory behind multilevel models are introduced, to illustrate how such models can be applied fruitfully in political science, and to call attention to some of the pitfalls in multileVEL analysis.
Book
The International Handbook of School Effectiveness Research
Charles Teddlie,David Reynolds +1 more
TL;DR: The Historical and Intellectual Foundations of School Effectiveness Research 1.An Introduction to school effectiveness research 2.Current Topics and Approaches in school effectiveness Research: The Contemporary Field Part Two: The Knowledge Base of school effectiveness research 3.The Methodology and Scientific Properties of School effectiveness research 4.The Processes of school effectiveness 5.Context Issues within school effectiveness as discussed by the authors.
Journal ArticleDOI
Application of Hierarchical Linear Models to Assessing Change
TL;DR: This article proposed a two-stage hierarchical linear model (HLM) to study the structure of individual growth and estimate important statistical and psychometric properties of collections of growth trajectories, discovering correlates of change factors that influence the rate at which individuals develop; and testing hypotheses about the effects of on or more experimental or quasi-experimental treatments on growth curves.
References
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Journal ArticleDOI
Maximum Likelihood Approaches to Variance Component Estimation and to Related Problems
TL;DR: In this paper, the authors proposed a restricted maximum likelihood (reml) approach which takes into account the loss in degrees of freedom resulting from estimating fixed effects, and developed a satisfactory asymptotic theory for estimators of variance components.
Book
Advances in factor analysis and structural equation models
TL;DR: The methods in this book do not provide final answers to the question of model specification but offer the researcher the flexibility to formulate and test a variety of causal models and to guide the analysis toward more adequate explanations of the relationships embedded in data.
Journal ArticleDOI
The theory of least squares when the parameters are stochastic and its application to the analysis of growth curves
TL;DR: In the present paper, a class of problems where the dispersion matrix has a known structure is considered and the appropriate statistical methods are discussed.
Journal ArticleDOI
Some contributions to efficient statistics in structural models: Specification and estimation of moment structures.
TL;DR: In this article, it is shown that higher order product moments yield important structural information when the distribution of variables is arbitrary, and some asymptotically distribution-free efficient estimators for such arbitrary structural models are developed.