Regression, weighting and related approaches to estimating a population mean from a sample with nonrandom missing data often rely on the assumption that conditional on covariates, observed samples can be treated as random. Standard methods using this assumption generally will fail to yield consistent estimators when covariates are measured with…

This study examines the use of cross-classified random effects models (CCrem) and cross-classified multiple membership random effects models (CCMMrem) to model rater bias and estimate teacher effectiveness. Effect estimates are compared using CTT versus item response theory (IRT) scaling methods and three models (i.e., conventional multilevel…

In recent years, many states have adopted Item Response Theory (IRT) based vertically scaled tests due to their compelling features in a growth-based accountability context. However, selection of a practical and effective calibration/scaling method and proper understanding of issues with possible multidimensionality in the test data is critical to…

This article investigates the use of teacher value-added estimates to assess the distribution of effective teaching across students of varying socioeconomic disadvantage in the presence of classroom composition effects. We examine, via simulations, how accurately commonly used teacher value-added estimators recover the rank correlation between…

The reliability of data is a critical issue in decision-making for practitioners in the school. Percent Agreement and Cohen's kappa are the two most widely reported indices of inter-rater reliability, however, a recent Monte Carlo study on the reliability of multi-category scales found other indices to be more trustworthy given the type of data…

Because random assignment is not possible in observational studies, estimates of treatment effects might be biased due to selection on observable and unobservable variables. To strengthen causal inference in longitudinal observational studies of multiple treatments, we present 4 latent growth models for propensity score matched groups, and…

A Monte Carlo simulation was conducted to investigate the robustness of 4 latent variable interaction modeling approaches (Constrained Product Indicator [CPI], Generalized Appended Product Indicator [GAPI], Unconstrained Product Indicator [UPI], and Latent Moderated Structural Equations [LMS]) under high degrees of nonnormality of the observed…