We present a bias-adjusted three-step estimation approach for multilevel latent class models (LC) with covariates. The proposed approach involves (1) fitting a single-level measurement model while ignoring the multilevel structure, (2) assigning units to latent classes, and (3) fitting the multilevel model with the covariates while controlling for…

A recent review found that 11% of published factor models are hierarchical models with second-order factors. However, dedicated recommendations for evaluating hierarchical model fit have yet to emerge. Traditional benchmarks like RMSEA <0.06 or CFI >0.95 are often consulted, but they were never intended to generalize to hierarchical models.…

Oftentimes in many fields of the social and natural sciences, data are obtained within a nested structure (e.g., students within schools). To effectively analyze data with such a structure, multilevel models are frequently employed. The present study utilizes a Monte Carlo simulation to compare several novel multilevel classification algorithms…

The cross-classified data structure is ubiquitous in education, psychology, and health outcome sciences. In these areas, assessment instruments that are made up of multiple items are frequently used to measure latent constructs. The presence of both the cross-classified structure and multivariate categorical outcomes leads to the so-called…

Cluster memberships associated with the mediation effect are often changed due to the temporal distance between the cause-and-effect variables in longitudinal data. Nevertheless, current practices in multilevel mediation analysis mostly assume a purely hierarchical data structure. A Monte Carlo simulation study is conducted to examine the…

Multilevel models are increasingly used in sociology and other social sciences to analyze variation of tie outcomes in egocentrically sampled network data, particularly in studies of social support. Existing research assumes that the personal networks in the data do not overlap (i.e., they do not have actors in common), which makes standard…

Disengaged item responses pose a threat to the validity of the results provided by large-scale assessments. Several procedures for identifying disengaged responses on the basis of observed response times have been suggested, and item response theory (IRT) models for response engagement have been proposed. We outline that response time-based…

Current practices for growth mixture modeling emphasize the importance of the proper parameterization and number of classes, but the impact of these decisions on latent class composition and the substantive implications has not been thoroughly addressed. Using measures of behavior from 575 middle school students, we compared the results of several…

This article presents a latent class model for multilevel data to identify latent subgroups and estimate heterogeneous treatment effects. Unlike sequential approaches that partition data first and then estimate average treatment effects (ATEs) within classes, we employ a Bayesian procedure to jointly estimate mixing probability, selection, and…

Policymakers have grown increasingly interested in how experimental results may generalize to a larger population. However, recently developed propensity score-based methods are limited by small sample sizes, where the experimental study is generalized to a population that is at least 20 times larger. This is particularly problematic for methods…

I analyze the effects of household sociodemography, interviewer performance in the current survey, and fieldwork characteristics on cooperation in a central telephone survey, where households with no publicly listed landline number receive face-to-face visits. Using the 2013 refreshment sample of the Swiss Household Panel, I employ…

Screening is necessary to detect risk and prevent reading failure. Yet the amount of screening that commonly occurs in U.S. schools may undermine its value, creating more error in decision making and lost instructional opportunity. This 2-year longitudinal study examined the decision accuracy associated with collecting concurrent reading screening…

This study investigates the influence of school sector (private versus state schools) and student gender on knowledge of native fauna. Our main objectives were (a) to describe the knowledge of high school students from the province of Cordoba, Argentina with respect to native animal species, (b) to determine if any exotic species (introduced or…

The multilevel latent class model (MLCM) is a multilevel extension of a latent class model (LCM) that is used to analyze nested structure data structure. The nonparametric version of an MLCM assumes a discrete latent variable at a higher-level nesting structure to account for the dependency among observations nested within a higher-level unit. In…

This article explores cross-national differences in the intensity of perceived barriers to adult learning in Europe focusing on the barriers recognised by those not participating and having no intention to do so. This relatively large subgroup has received scant scholarly attention, yet exploring their participation barriers is critical for…