The aim of this longitudinal study is to evaluate 3 views on the relationship between nonword repetition and vocabulary: (i) the storage-based view that considers nonword repetition, a measure of phonological storage, as the driving force behind vocabulary development, (ii) the lexical restructuring view that considers improvements in nonword…

Among predictors of second language (L2) reading, both first language (L1) reading and L2 listening embody the complexities of comprehension ability in their construct. Their contributions to L2 reading have rarely been examined together, probably because of the different theoretical frameworks in which they are postulated. Therefore, the field…

Frequent social interactions are strongly linked to positive affect, longevity, and good health. Although there has been extensive research on changes in the size of social networks over time, little attention has been given to the development of contact frequency across the life span. In this cohort-sequential longitudinal study, we examined…

We investigated methods of including covariates in two-level models for cluster randomized trials to increase power to detect the treatment effect. We compared multilevel models that included either an observed cluster mean or a latent cluster mean as a covariate, as well as the effect of including Level 1 deviation scores in the model. A Monte…

A distinction is proposed between measures and predictors of latent variables. The discussion addresses the consequences of the distinction for the true-score model, the linear factor model, Structural Equation Models, longitudinal and multilevel models, and item-response models. A distribution-free treatment of calibration and…

A crucial issue in the European Union (EU) is which policies should be regulated by EU and which ones by national governments. Given this situation it is interesting to study the citizens' preference for the level of political decision making. The interest of the paper is mainly empirical, which consists in the creation of a measure for…

This study introduces three growth modeling techniques: latent growth modeling (LGM), hierarchical linear modeling (HLM), and longitudinal profile analysis via multidimensional scaling (LPAMS). It compares the multilevel growth parameter estimates and potential predictor effects obtained using LGM, HLM, and LPAMS. The purpose of this multilevel…

A unifying framework for generalized multilevel structural equation modeling is introduced. The models in the framework, called generalized linear latent and mixed models (GLLAMM), combine features of generalized linear mixed models (GLMM) and structural equation models (SEM) and consist of a response model and a structural model for the latent…