Simple matrix sampling planned missing (SMS PD) design, introduce missing data patterns that lead to covariances between variables that are not jointly observed, and create difficulties for analyses other than mean and variance estimations. Based on prior research, we adopted a new multigroup confirmatory factor analysis (CFA) approach to handle…

Small sample sizes contribute to several problems in research and knowledge advancement. This conceptual replication study confirmed and extended the inflation of type II errors and confidence intervals in correlation analyses of small sample sizes common in kinesiology/exercise science. Current population data (N = 18, 230, & 464) on four…

The Q-matrix played a key role in implementations of diagnostic classification models (DCMs) or cognitive diagnostic models (CDMs) -- a family of psychometric models that are gaining attention in providing diagnostic information on students' mastery of cognitive attributes or skills. Using two Monte Carlo simulation studies, this dissertation…

This article develops new closed-form variance expressions for power analyses for commonly used difference-in-differences (DID) and comparative interrupted time series (CITS) panel data estimators. The main contribution is to incorporate variation in treatment timing into the analysis. The power formulas also account for other key design features…

The purpose of this study is to show how Monte Carlo analysis of meta-analytic estimators can be used to select estimators for specific research situations. Our analysis conducts 1620 individual experiments, where each experiment is defined by a unique combination of sample size, effect size, effect size heterogeneity, publication selection…

The use of multilevel modeling (MLM) to analyze nested data has grown in popularity over the years in the study of school psychology. However, with the increase in use, several statistical misconceptions about the technique have also proliferated. We discuss some commonly cited myths and golden rules related to the use of MLM, explain their…

Experimentation is the foundation of science and an important process for students to understand and experience. However, it can be difficult to teach some aspects of experimentation within the time and resource constraints of an academic semester. Interactive models can be a useful tool in bridging this gap. This freely accessible simulation…

In education research, small samples are common because of financial limitations, logistical challenges, or exploratory studies. With small samples, statistical principles on which researchers rely do not hold, leading to trust issues with model estimates and possible replication issues when scaling up. Researchers are generally aware of such…

Evaluators of education interventions are increasingly designing studies to detect impacts much smaller than the 0.20 standard deviations that Cohen (1988) characterized as "small." While the need to detect smaller impacts is based on compelling arguments that such impacts are substantively meaningful, the drive to detect smaller impacts…

Researchers often use generalizability theory to estimate relative error variance and reliability in teaching observation measures. They also use it to plan future studies and design the best possible measurement procedures. However, designing the best possible measurement procedure comes at a cost, and researchers must stay within their budget…

Educational researchers commonly use the rule of thumb of "design effect smaller than 2" as the justification of not accounting for the multilevel or clustered structure in their data. The rule, however, has not yet been systematically studied in previous research. In the present study, we generated data from three different models…

In some instances, intentionally or not, study designs are such that there is clustering in one group but not in the other. This paper describes methods for computing effect size estimates and their variances when there is clustering in only one group and the analysis has not taken that clustering into account. The authors provide the effect size…

Research designs involving cluster randomization are becoming increasingly important in educational and behavioral research. Many of these designs involve two levels of clustering or nesting (students within classes and classes within schools). Researchers would like to compute effect size indexes based on the standardized mean difference to…

This article proposes that sampling design effects have potentially huge unrecognized impacts on the results reported by large-scale district and state assessments in the United States. When design effects are unrecognized and unaccounted for they lead to underestimating the sampling error in item and test statistics. Underestimating the sampling…

This methodological brief introduces the readers to the propensity score matching method, which can be used for enhancing the validity of causal inferences in research situations involving nonexperimental design or observational research, or in situations where the benefits of an experimental design are not fully realized because of reasons beyond…