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Ben Kelcey; Fangxing Bai; Amota Ataneka; Yanli Xie; Kyle Cox – Society for Research on Educational Effectiveness, 2024
We consider a class of multiple-group individually-randomized group trials (IRGTs) that introduces a (partially) cross-classified structure in the treatment condition (only). The novel feature of this design is that the nature of the treatment induces a clustering structure that involves two or more non-nested groups among individuals in the…
Descriptors: Randomized Controlled Trials, Research Design, Statistical Analysis, Error of Measurement
Qian Zhang; Qi Wang – Structural Equation Modeling: A Multidisciplinary Journal, 2024
In the article, we focused on the issues of measurement error and omitted confounders while conducting mediation analysis under experimental studies. Depending on informativeness of the confounders between the mediator (M) and outcome (Y), we described two approaches. When researchers are confident that primary confounders are included (e.g.,…
Descriptors: Error of Measurement, Research and Development, Mediation Theory, Causal Models
Huang, Francis L. – Journal of Educational and Behavioral Statistics, 2022
The presence of clustered data is common in the sociobehavioral sciences. One approach that specifically deals with clustered data but has seen little use in education is the generalized estimating equations (GEEs) approach. We provide a background on GEEs, discuss why it is appropriate for the analysis of clustered data, and provide worked…
Descriptors: Multivariate Analysis, Computation, Correlation, Error of Measurement
A. E. Ades; Nicky J. Welton; Sofia Dias; David M. Phillippo; Deborah M. Caldwell – Research Synthesis Methods, 2024
Network meta-analysis (NMA) is an extension of pairwise meta-analysis (PMA) which combines evidence from trials on multiple treatments in connected networks. NMA delivers internally consistent estimates of relative treatment efficacy, needed for rational decision making. Over its first 20 years NMA's use has grown exponentially, with applications…
Descriptors: Network Analysis, Meta Analysis, Medicine, Clinical Experience
Kaltsonoudi, Kalliope; Tsigilis, Nikolaos; Karteroliotis, Konstantinos – Measurement in Physical Education and Exercise Science, 2022
Common method variance refers to the amount of uncontrolled systematic error leading to biased estimates of scale reliability and validity and to spurious covariance shared among variables due to common method and/or common source employed in survey-based researches. As the extended use of self-report questionnaires is inevitable, numerous studies…
Descriptors: Athletics, Research, Research Methodology, Error of Measurement
Penaloza, Roberto V.; Berends, Mark – Sociological Methods & Research, 2022
To measure "treatment" effects, social science researchers typically rely on nonexperimental data. In education, school and teacher effects on students are often measured through value-added models (VAMs) that are not fully understood. We propose a framework that relates to the education production function in its most flexible form and…
Descriptors: Data, Value Added Models, Error of Measurement, Correlation
Levin, Joel R.; Ferron, John M.; Gafurov, Boris S. – Journal of Education for Students Placed at Risk, 2022
The present simulation study examined the statistical properties (namely, Type I error and statistical power) of various novel randomized single-case multiple-baseline designs and associated randomized-test analyses for comparing the A- to B-phase immediate abrupt outcome changes in two independent intervention conditions. It was found that with…
Descriptors: Statistical Analysis, Error of Measurement, Intervention, Program Effectiveness
John R. Donoghue; Carol Eckerly – Applied Measurement in Education, 2024
Trend scoring constructed response items (i.e. rescoring Time A responses at Time B) gives rise to two-way data that follow a product multinomial distribution rather than the multinomial distribution that is usually assumed. Recent work has shown that the difference in sampling model can have profound negative effects on statistics usually used to…
Descriptors: Scoring, Error of Measurement, Reliability, Scoring Rubrics
Suyoung Kim; Sooyong Lee; Jiwon Kim; Tiffany A. Whittaker – Structural Equation Modeling: A Multidisciplinary Journal, 2024
This study aims to address a gap in the social and behavioral sciences literature concerning interaction effects between latent factors in multiple-group analysis. By comparing two approaches for estimating latent interactions within multiple-group analysis frameworks using simulation studies and empirical data, we assess their relative merits.…
Descriptors: Social Science Research, Behavioral Sciences, Structural Equation Models, Statistical Analysis
Kulinskaya, Elena; Hoaglin, David C. – Research Synthesis Methods, 2023
For estimation of heterogeneity variance T[superscript 2] in meta-analysis of log-odds-ratio, we derive new mean- and median-unbiased point estimators and new interval estimators based on a generalized Q statistic, Q[subscript F], in which the weights depend on only the studies' effective sample sizes. We compare them with familiar estimators…
Descriptors: Q Methodology, Statistical Analysis, Meta Analysis, Intervals
Buckley, Jeffrey; Hyland, Tomás; Seery, Niall – International Journal of Technology and Design Education, 2023
Technology education research is a growing field, with the rate of growth increasing over the last 2 decades. As the field grows, it is paramount that credibility is maintained in published findings. To date there is no evidence to suggest a lack trust is warranted, however in the midst of the replication crisis there is need to ensure continued…
Descriptors: Technology Education, Educational Research, Replication (Evaluation), Credibility
Wendy Chan; Larry Vernon Hedges – Journal of Educational and Behavioral Statistics, 2022
Multisite field experiments using the (generalized) randomized block design that assign treatments to individuals within sites are common in education and the social sciences. Under this design, there are two possible estimands of interest and they differ based on whether sites or blocks have fixed or random effects. When the average treatment…
Descriptors: Research Design, Educational Research, Statistical Analysis, Statistical Inference
Campbell, Harlan; de Jong, Valentijn M. T.; Maxwell, Lauren; Jaenisch, Thomas; Debray, Thomas P. A.; Gustafson, Paul – Research Synthesis Methods, 2021
Ideally, a meta-analysis will summarize data from several unbiased studies. Here we look into the less than ideal situation in which contributing studies may be compromised by non-differential measurement error in the exposure variable. Specifically, we consider a meta-analysis for the association between a continuous outcome variable and one or…
Descriptors: Error of Measurement, Meta Analysis, Bayesian Statistics, Statistical Analysis
Dan Soriano; Eli Ben-Michael; Peter Bickel; Avi Feller; Samuel D. Pimentel – Grantee Submission, 2023
Assessing sensitivity to unmeasured confounding is an important step in observational studies, which typically estimate effects under the assumption that all confounders are measured. In this paper, we develop a sensitivity analysis framework for balancing weights estimators, an increasingly popular approach that solves an optimization problem to…
Descriptors: Statistical Analysis, Computation, Mathematical Formulas, Monte Carlo Methods
Emma Somer; Carl Falk; Milica Miocevic – Structural Equation Modeling: A Multidisciplinary Journal, 2024
Factor Score Regression (FSR) is increasingly employed as an alternative to structural equation modeling (SEM) in small samples. Despite its popularity in psychology, the performance of FSR in multigroup models with small samples remains relatively unknown. The goal of this study was to examine the performance of FSR, namely Croon's correction and…
Descriptors: Scores, Structural Equation Models, Comparative Analysis, Sample Size