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…

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…

During the 2005-06 school year, more than 6.7 million children with disabilities received special education and related services in our public schools; this represents more than a 20 percent increase over the previous decade (U.S. Department of Education, 2009). These children, who are typically at risk for chronic physical, developmental,…