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Pablo A. Mitnik – Sociological Methods & Research, 2025
Although there is an extensive methodological literature on the measurement of intergenerational income mobility, there has been limited research on the conceptual interpretation of mobility measures and the methodological implications of those interpretations. In this article, I focus on the three measures of mobility most frequently used in the…
Descriptors: Social Mobility, Income, Correlation, Measurement Techniques
Su, Hsu-Lin; Chen, Po-Hsi – Educational and Psychological Measurement, 2023
The multidimensional mixture data structure exists in many test (or inventory) conditions. Heterogeneity also relatively exists in populations. Still, some researchers are interested in deciding to which subpopulation a participant belongs according to the participant's factor pattern. Thus, in this study, we proposed three analysis procedures…
Descriptors: Data Analysis, Correlation, Classification, Factor Structure
Alexander Robitzsch; Oliver Lüdtke – Structural Equation Modeling: A Multidisciplinary Journal, 2025
The random intercept cross-lagged panel model (RICLPM) decomposes longitudinal associations between two processes X and Y into stable between-person associations and temporal within-person changes. In a recent study, Bailey et al. demonstrated through a simulation study that the between-person variance components in the RICLPM can occur only due…
Descriptors: Longitudinal Studies, Correlation, Time, Simulation
John Mart V. DelosReyes; Miguel A. Padilla – Journal of Experimental Education, 2024
Estimating confidence intervals (CIs) for the correlation has been a challenge because the correlation sampling distribution changes depending on the correlation magnitude. The Fisher z-transformation was one of the first attempts at estimating correlation CIs but has historically shown to not have acceptable coverage probability if data were…
Descriptors: Research Problems, Correlation, Intervals, Computation
Idam Ragil Widianto Atmojo; Roy Ardiansyah; Joko Tri Widianto – Elementary School Forum (Mimbar Sekolah Dasar), 2024
This study aims to determine whether there is a relationship between linguistic intelligence and computational thinking. The research method employed is quantitative, utilizing a correlational research design. The research sample comprised 73 students from 4 elementary schools in the Laweyan District, Surakarta City. Data collection involved a…
Descriptors: Intelligence, Linguistics, Computation, Grade 5
Julia-Kim Walther; Martin Hecht; Steffen Zitzmann – Structural Equation Modeling: A Multidisciplinary Journal, 2025
Small sample sizes pose a severe threat to convergence and accuracy of between-group level parameter estimates in multilevel structural equation modeling (SEM). However, in certain situations, such as pilot studies or when populations are inherently small, increasing samples sizes is not feasible. As a remedy, we propose a two-stage regularized…
Descriptors: Sample Size, Hierarchical Linear Modeling, Structural Equation Models, Matrices
Neveu, Maëlle; Geurten, Marie; Durieux, Nancy; Rousselle, Laurence – Educational Psychology Review, 2023
Although the role played by finger use in children's numerical development has been widely investigated, their benefit in arithmetical contexts is still debated today. This scoping review aimed to systematically identify and summarize all studies that have investigated the relation between fingers and arithmetic skills in children. An extensive…
Descriptors: Human Body, Arithmetic, Mathematics Skills, Children
Guangjian Zhang; Lauren A. Trichtinger; Dayoung Lee; Ge Jiang – Structural Equation Modeling: A Multidisciplinary Journal, 2022
Many applications of structural equation modeling involve ordinal (e.g., Likert) variables. A popular way of dealing with ordinal variables is to estimate the model with polychoric correlations rather than Pearson correlations. Such an estimation also requires the asymptotic covariance matrix of polychoric correlations. It is computationally…
Descriptors: Structural Equation Models, Predictor Variables, Correlation, Computation
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
Jessica M. Namkung; Peng Peng; Marc J. Goodrich – Learning Disability Quarterly, 2025
This study is a secondary analysis of the data collected in a randomized control trial study with sixth graders with mathematics learning difficulties (MLDs). We explored the relation between mathematics anxiety and mathematics performance for students with and without MLD. We further explored whether mathematics vocabulary and computational…
Descriptors: Mathematics Anxiety, Mathematics Skills, Correlation, Students with Disabilities
Doran, Harold – Journal of Educational and Behavioral Statistics, 2023
This article is concerned with a subset of numerically stable and scalable algorithms useful to support computationally complex psychometric models in the era of machine learning and massive data. The subset selected here is a core set of numerical methods that should be familiar to computational psychometricians and considers whitening transforms…
Descriptors: Scaling, Algorithms, Psychometrics, Computation
Ehri Ryu – Society for Research on Educational Effectiveness, 2024
Background/Context: Confirmatory factor analysis (CFA) model is a commonly adopted framework to estimate and test a measurement model. Once a well-fitting final CFA model is selected, the selected model may be used to test structural relationships of the latent constructs with other variables, to construct a test with desired reliability and…
Descriptors: Research Problems, Factor Analysis, Scores, Computation
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
Nihumathunnisa H.; Jahitha Begum A.; Sathishkumar A. – Journal on Educational Psychology, 2025
Executive functioning skills are very essential components of effective learning, innovative thinking, and decision-making that are necessary for the growing minds of the twenty-first century. Executive functioning refers to the collection of mental processes that guide and control psychological behavior and activities. Working memory, attentional…
Descriptors: Executive Function, Computation, Thinking Skills, Academic Achievement
Kenneth A. Frank; Qinyun Lin; Spiro Maroulis – Grantee Submission, 2023
Beginning with debates about the effects of smoking on lung cancer, sensitivity analyses characterizing the hypothetical unobserved conditions that can alter statistical inferences have had profound impacts on public policy. One of the most ascendant techniques for sensitivity analysis is Oster's (2019) coefficient of proportionality, which…
Descriptors: Computation, Statistical Analysis, Statistical Inference, Correlation

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