The use of multilevel modeling with data from population-based surveys is often limited by the small number of cases per Level 2 unit, prompting a recent trend in the neighborhood literature to apply cluster techniques to address the problem of data sparseness. In this study, the authors use...

Two-level theories explain outcomes with causal variables at two levels of analysis that are systematically related to one another. Although many prominent scholars in the field of comparative analysis have developed two-level theories, the empirical and methodological issues that these theories...

The authors study alternative estimators of the impacts of higher level variables in multilevel models. This is important since many of the important variables in social science research are higher level factors having impacts on many lower level outcomes such as school achievement and...

For the cluster randomized trial, the treatment, implemented at the cluster level, may be hypothesized to impact a final outcome of interest via a mediating variable, with the mediator and outcome being measured typically at the participant level. Two opposing views—one that allows the...

Definitions of direct and indirect effects are given for settings in which individuals are clustered in groups or neighborhoods and in which treatments are administered at the group level. A particular intervention may affect individual outcomes both through its effect on the individual and by...

Population-based surveys are of limited utility to estimate rare or low-incidence groups, particularly for those defined by religion or ethnicity not included in the U.S. Census. Methods of cross-survey analysis and small area estimation, however, can be used to provide reliable estimates of...