This study investigated the extent to which class-specific parameter estimates are biased by the within-class normality assumption in nonnormal growth mixture modeling (GMM). Monte Carlo simulations for nonnormal GMM were conducted to analyze and compare two strategies for obtaining unbiased parameter estimates: relaxing the within-class normality…

Analysts of discrete data often face the challenge of managing the tendency of inflation on certain values. When treated improperly, such phenomenon may lead to biased estimates and incorrect inferences. This study extends the existing literature on single-value inflated models and develops a general framework to handle variables with more than…

Despite broad applications of growth curve models, few studies have dealt with a practical issue -- nonnormality of data. Previous studies have used Student's "t" distributions to remedy the nonnormal problems. In this study, robust distributional growth curve models are proposed from a semiparametric Bayesian perspective, in which…

Growth curve models are widely used in social and behavioral sciences. However, typical growth curve models often assume that the errors are normally distributed although non-normal data may be even more common than normal data. In order to avoid possible statistical inference problems in blindly assuming normality, a general Bayesian framework is…

Typically a longitudinal growth modeling based on item response theory (IRT) requires repeated measures data from a single group with the same test design. If operational or item exposure problems are present, the same test may not be employed to collect data for longitudinal analyses and tests at multiple time points are constructed with unique…

This large-scale, longitudinal study examines teacher attrition data from over 6,500 teachers in Illinois over a 14-year period from 1997 to 2010. Attrition rates between teachers who participated in a Professional Development School (PDS) versus students prepared traditionally are compared. The effects of teacher preparation experiences on…

In this study, we tested the outcomes of access to a response to intervention (RtI) model in kindergarten or in first grade on end-of-Grade-2 reading achievement and placement in special education. Across five schools, 214 students who began having access to Tier 2 intervention in kindergarten or first grade were compared in Grades 1 and 2 with…

In this study, we tested the outcomes of access to a Response to Intervention (RtI) model in kindergarten or in first grade on end-of-Grade-2 reading achievement and placement in special education. Across five schools, 214 students who began having access to Tier 2 intervention in kindergarten or first grade were compared in Grades 1 and 2 with…

Background: Despite a powerful civil rights movement and legislation barring discrimination in housing markets, residential neighborhoods remain racially segregated. Purpose: This study examines the extent to which neighborhoods' racial composition is inherited across generations and the extent to which high schools' and colleges' racial…

A general diagnostic model was used to specify and compare two multidimensional item-response-theory (MIRT) models for longitudinal data: (a) a model that handles repeated measurements as multiple, correlated variables over time (Andersen, 1985) and (b) a model that assumes one common variable over time and additional orthogonal variables that…