Multilevel modeling is a technique that has numerous potential applications for social and personality psychology. To help realize this potential, this article provides an introduction to multilevel modeling with an emphasis on some of its applications in social and personality psychology. This introduction includes a description of multilevel modeling, a rationale for this technique, and a dis...

Multilevel (hierarchical) modeling is a generalization of linear and generalized linear modeling in which regression coefficients are themselves given a model, whose parameters are also estimated from data. We illustrate the strengths and limitations of multilevel modeling through an example of the prediction of home radon levels in U.S. counties. The multilevel model is highly effective for pr...

Recent developments in the collection and modeling of intensive longitudinal data have enabled us to fit dynamic twin models, which within-person processes are separated into genetic environ...

Previous work has shown that multilevel modeling can be a valuable technique for epidemiologic analysis. The complexity of using this approach, however, continues to restrict its general application. A critical factor is the lack of flexible and appropriate software for multilevel modeling. SAS provides a macro, GLIMMIX, that can be used for multilevel modeling, but that is not sufficient for a...

Modelling strategies for value-added multilevel models are examined. These types of models typically include an endogenous variable and this causes difficulties for the standard estimation techniques that are commonly used to analyse multilevel models. Two alternative estimation strategies are proposed: one using an instrumental variable approach and the other using a Bayesian analysis as avail...

This paper employs a three-level hierarchical linear model (HLM) to examine the impacts that the quality of the environment and neighbourhood affluence have on housing prices. The empirical results suggest that there are significant variations in the average housing price for different neighbourhoods and administrative districts. The impact of building characteristics on housing prices is subje...

Traditional study designs, such as individual-level studies and ecological studies, are unable to simultaneously examine the effects of individual-level and group-level factors on risk of disease. Multilevel analysis overcomes this limitation by allowing the simultaneous investigation of factors defined at multiple levels. Areas in which multilevel modeling can be applied to sexually transmitte...

Multilevel modeling (MLM) is frequently used to detect group differences, such as an intervention effect in a pre-test–post-test cluster-randomized design. Group differences on the post-test scores are detected by controlling for pre-test scores as a proxy variable for unobserved factors that predict future attributes. The pre-test and post-test scores that are most often used in MLM are summed...

The classical multitrait-multimethod (MTMM) matrix can be viewed as a two-dimensional cross-classification of traits and methods. Beside commonly used analysis methods such as structural equation modeling and generalizability theory, multilevel analysis offers attractive possibilities. If the focus is only on analyzing classical MTMM data, the multilevel approach has no surplus value, because t...

Introduction ......................................................................................................... 390 Data ...................................................................................................................... 391 PIRLS ................................................................................................................ 391 Plausible Value Outcome...