This study aims to compare item and student parameters of dichotomously scored multidimensional constructs estimated based on unidimensional and multidimensional Item Response Theory (IRT) under different conditions of sample size, interdimensional correlation and number of dimensions. This research, conducted with simulations, is of a basic…

Differential item functioning (DIF) often arises from multiple sources. Within the context of multidimensional item response theory, this study examined DIF items with varying secondary dimensions using the three DIF methods: SIBTEST, Mantel-Haenszel, and logistic regression. The effect of the number of secondary dimensions on DIF detection rates…

A Monte Carlo study was conducted to compare the performance of a level-specific (LS) fit evaluation with that of a simultaneous (SI) fit evaluation in multilevel confirmatory factor analysis (MCFA) models. We extended previous studies by examining their performance under MCFA models with different factor structures across levels. In addition,…

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…

It is common to include multiple dependent variables (DVs) in single-case experimental design (SCED) meta-analyses. However, statistical issues associated with multiple DVs in the multilevel modeling approach (i.e., possible dependency of error, heterogeneous treatment effects, and heterogeneous error structures) have not been fully investigated.…

Synthesizing findings about the indirect (mediated) effect plays an important role in determining the mechanism through which variables affect one another. This simulation study compared six methods for synthesizing indirect effects: correlation-based MASEM, parameter-based MASEM, marginal likelihood synthesis, an adjustment to marginal likelihood…

When the relationship between two physical variables, such as voltage and current, can be expressed as y = bx where b is a constant. b may be estimated by least squares, or by averaging the values of b obtained for each x-y data pair. We show for data gathered in an experiment, as well as through Monte Carlo simulation and mathematical analysis,…

Exploratory factor analysis (EFA) is widely used by researchers in the social sciences to characterize the latent structure underlying a set of observed indicator variables. One of the primary issues that must be resolved when conducting an EFA is determination of the number of factors to retain. There exist a large number of statistical tools…

For decades, achievement goal theory has been extensively used, but empirical research still requires a clearer understanding of the underlying factors conceptualized and measured during secondary school periods. In light of the increasing use of longitudinal studies in motivation research, this study aims to investigate the longitudinal…

In this article, we present the results of three question design experiments on inter-item correlations, which tested a grid design against a single-item design. The first and second experiments examined the inter-item correlations of a set with five and seven items, respectively, and the third experiment examined the impact of the question design…

This dissertation investigates the inequitable distribution and causal impacts of mathematics teachers' content knowledge for teaching (CKT) on instructional quality and student learning outcomes. Using the rich information in the Measures of Effective Teaching (MET) project longitudinal database, the study addresses three core research questions:…

Collection and analysis of longitudinal data is an important tool in understanding growth and development over time in a whole range of human endeavors. Ideally, researchers working in the longitudinal framework are able to collect data at more than two points in time, as this will provide them with the potential for a deeper understanding of the…

Objective: Various statistical methods have been developed to estimate hazard ratios (HRs) from published Kaplan-Meier (KM) curves for the purpose of performing meta-analyses. The objective of this study was to determine the reliability, accuracy, and precision of four commonly used methods by Guyot, Williamson, Parmar, and Hoyle and Henley.…

Studies analyzing clustered data sets using both multilevel models (MLMs) and ordinary least squares (OLS) regression have generally concluded that resulting point estimates, but not the standard errors, are comparable with each other. However, the accuracy of the estimates of OLS models is important to consider, as several alternative techniques…

Researchers continue to be interested in efficient, accurate methods of estimating coefficients of covariates in mixture modeling. Including covariates related to the latent class analysis not only may improve the ability of the mixture model to clearly differentiate between subjects but also makes interpretation of latent group membership more…