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…

Nonnormality of univariate data has been extensively examined previously (Blanca et al., 2013; Micceri, 1989). However, less is known of the potential nonnormality of multivariate data although multivariate analysis is commonly used in psychological and educational research. Using univariate and multivariate skewness and kurtosis as measures of…

In this article, we review four software packages for implementing propensity score analysis in R: "Matching, MatchIt, PSAgraphics," and "twang." After briefly discussing essential elements for propensity score analysis, we apply each package to a data set from the Early Childhood Longitudinal Study in order to estimate the…

Complex surveys are often used to estimate causal effects regarding the effects of interventions or exposures of interest. Propensity scores (Rosenbaum & Rubin, 1983) have emerged as one popular and effective tool for causal inference in non-experimental studies, as they can help ensure that groups being compared are similar with respect to a…

Growth curve modeling provides a general framework for analyzing longitudinal data from social, behavioral, and educational sciences. Bayesian methods have been used to estimate growth curve models, in which priors need to be specified for unknown parameters. For the covariance parameter matrix, the inverse Wishart prior is most commonly used due…

In observational studies, selection bias will be completely removed only if the selection mechanism is ignorable, namely, all confounders of treatment selection and potential outcomes are reliably measured. Ideally, well-grounded substantive theories about the selection process and outcome-generating model are used to generate the sample of…

Often it is infeasible or unethical to use random assignment in educational settings to study important constructs and questions. Hence, educational research often uses observational data, such as large-scale secondary data sets and state and school district data, and quasi-experimental designs. One method of reducing selection bias in estimations…

Researchers have become increasingly interested in programs' main and interaction effects of two variables (A and B, e.g., two treatment variables or one treatment variable and one moderator) on outcomes. A challenge for estimating main and interaction effects is to eliminate selection bias across A-by-B groups. I introduce Rubin's causal model to…

This paper is based on previous studies in applying propensity score methods to study multiple treatment variables to examine the causal moderator effect. The propensity score methods will be demonstrated in a case study to examine the causal moderator effect, where the moderators are categorical and continuous variables. Moderation analysis is an…

Determining the effectiveness of many special education interventions is most difficult because of the practical and ethical limitations associated with assigning participants to a control or non-treated group. Using Longitudinal Study of Australian Children data, this article utilised eight different propensity score analysis methods to determine…

Propensity score analysis (PSA) has been used in a variety of settings, such as education, epidemiology, and sociology. Most typically, propensity score analysis has been implemented within the conventional frequentist perspective of statistics. This perspective, as is well known, does not account for uncertainty in either the parameters of the…

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…

Rates of food insecurity in households with children have significantly increased over the past decade. The majority of children, including those at risk for food insecurity, participate in some form of non-parental child care during the preschool years. To evaluate the relationship between the two phenomenon, this study investigates the effects…

Experiments that assign intact groups to treatment conditions are increasingly common in social research. In educational research, the groups assigned are often schools. The design of group-randomized experiments requires knowledge of the intraclass correlation structure to compute statistical power and sample sizes required to achieve adequate…