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Christian Röver; David Rindskopf; Tim Friede – Research Synthesis Methods, 2024
The trace plot is seldom used in meta-analysis, yet it is a very informative plot. In this article, we define and illustrate what the trace plot is, and discuss why it is important. The Bayesian version of the plot combines the posterior density of [tau], the between-study standard deviation, and the shrunken estimates of the study effects as a…
Descriptors: Graphs, Meta Analysis, Bayesian Statistics, Visualization
Sy Han Chiou; Gongjun Xu; Jun Yan; Chiung-Yu Huang – Grantee Submission, 2023
Recurrent event analyses have found a wide range of applications in biomedicine, public health, and engineering, among others, where study subjects may experience a sequence of event of interest during follow-up. The R package reReg offers a comprehensive collection of practical and easy-to-use tools for regression analysis of recurrent events,…
Descriptors: Data Analysis, Computer Software, Regression (Statistics), Models
Michael Schultz – Sociological Methods & Research, 2024
This paper presents a model of recurrent multinomial sequences. Though there exists a quite considerable literature on modeling autocorrelation in numerical data and sequences of categorical outcomes, there is currently no systematic method of modeling patterns of recurrence in categorical sequences. This paper develops a means of discovering…
Descriptors: Research Methodology, Sequential Approach, Models, Markov Processes
van Aert, Robbie C. M.; Goos, Cas – Research Synthesis Methods, 2023
The partial correlation coefficient quantifies the relationship between two variables while taking into account the effect of one or multiple control variables. Researchers often want to synthesize partial correlation coefficients in a meta-analysis since these can be readily computed based on the reported results of a linear regression analysis.…
Descriptors: Computation, Sampling, Correlation, Meta Analysis
William R. Dardick; Jeffrey R. Harring – Journal of Educational and Behavioral Statistics, 2025
Simulation studies are the basic tools of quantitative methodologists used to obtain empirical solutions to statistical problems that may be impossible to derive through direct mathematical computations. The successful execution of many simulation studies relies on the accurate generation of correlated multivariate data that adhere to a particular…
Descriptors: Statistics, Statistics Education, Problem Solving, Multivariate Analysis
Sang-June Park; Youjae Yi – Journal of Educational and Behavioral Statistics, 2024
Previous research explicates ordinal and disordinal interactions through the concept of the "crossover point." This point is determined via simple regression models of a focal predictor at specific moderator values and signifies the intersection of these models. An interaction effect is labeled as disordinal (or ordinal) when the…
Descriptors: Interaction, Predictor Variables, Causal Models, Mathematical Models
Raggi, Martina; Stanghellini, Elena; Doretti, Marco – Sociological Methods & Research, 2023
The decomposition of the overall effect of a treatment into direct and indirect effects is here investigated with reference to a recursive system of binary random variables. We show how, for the single mediator context, the marginal effect measured on the log odds scale can be written as the sum of the indirect and direct effects plus a residual…
Descriptors: Path Analysis, Student Attitudes, Museums, Error of Measurement
Andersson, Gustaf; Yang-Wallentin, Fan – Educational and Psychological Measurement, 2021
Factor score regression has recently received growing interest as an alternative for structural equation modeling. However, many applications are left without guidance because of the focus on normally distributed outcomes in the literature. We perform a simulation study to examine how a selection of factor scoring methods compare when estimating…
Descriptors: Regression (Statistics), Statistical Analysis, Computation, Scoring
Zachary K. Collier; Minji Kong; Olushola Soyoye; Kamal Chawla; Ann M. Aviles; Yasser Payne – Journal of Educational and Behavioral Statistics, 2024
Asymmetric Likert-type items in research studies can present several challenges in data analysis, particularly concerning missing data. These items are often characterized by a skewed scaling, where either there is no neutral response option or an unequal number of possible positive and negative responses. The use of conventional techniques, such…
Descriptors: Likert Scales, Test Items, Item Analysis, Evaluation Methods
Soojin Park; Xu Qin; Chioun Lee – Sociological Methods & Research, 2024
In the field of disparities research, there has been growing interest in developing a counterfactual-based decomposition analysis to identify underlying mediating mechanisms that help reduce disparities in populations. Despite rapid development in the area, most prior studies have been limited to regression-based methods, undermining the…
Descriptors: Medical Research, Research Methodology, Social Differences, Human Body
Long, J. Scott; Mustillo, Sarah A. – Sociological Methods & Research, 2021
Methods for group comparisons using predicted probabilities and marginal effects on probabilities are developed for regression models for binary outcomes. Unlike approaches based on the comparison of regression coefficients across groups, the methods we propose are unaffected by the scalar identification of the coefficients and are expressed in…
Descriptors: Regression (Statistics), Comparative Analysis, Probability, Groups
Angrist, Joshua – National Bureau of Economic Research, 2022
The view that empirical strategies in economics should be transparent and credible now goes almost without saying. The local average treatment effects (LATE) framework for causal inference helped make this so. The LATE theorem tells us for whom particular instrumental variables (IV) and regression discontinuity estimates are valid. This lecture…
Descriptors: Economics, Statistical Analysis, Causal Models, Regression (Statistics)
Lee, Yi-Hsuan; Haberman, Shelby J. – Journal of Educational Measurement, 2021
For assessments that use different forms in different administrations, equating methods are applied to ensure comparability of scores over time. Ideally, a score scale is well maintained throughout the life of a testing program. In reality, instability of a score scale can result from a variety of causes, some are expected while others may be…
Descriptors: Scores, Regression (Statistics), Demography, Data
Kjorte Harra; David Kaplan – Structural Equation Modeling: A Multidisciplinary Journal, 2024
The present work focuses on the performance of two types of shrinkage priors--the horseshoe prior and the recently developed regularized horseshoe prior--in the context of inducing sparsity in path analysis and growth curve models. Prior research has shown that these horseshoe priors induce sparsity by at least as much as the "gold…
Descriptors: Structural Equation Models, Bayesian Statistics, Regression (Statistics), Statistical Inference
Sinharay, Sandip – Journal of Educational and Behavioral Statistics, 2022
Takers of educational tests often receive proficiency levels instead of or in addition to scaled scores. For example, proficiency levels are reported for the Advanced Placement (AP®) and U.S. Medical Licensing examinations. Technical difficulties and other unforeseen events occasionally lead to missing item scores and hence to incomplete data on…
Descriptors: Computation, Data Analysis, Educational Testing, Accuracy