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Showing 1 to 15 of 450 results Save | Export
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Yan Xia; Xinchang Zhou – Educational and Psychological Measurement, 2025
Parallel analysis has been considered one of the most accurate methods for determining the number of factors in factor analysis. One major advantage of parallel analysis over traditional factor retention methods (e.g., Kaiser's rule) is that it addresses the sampling variability of eigenvalues obtained from the identity matrix, representing the…
Descriptors: Factor Analysis, Statistical Analysis, Evaluation Methods, Sampling
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Hsin-Yun Lee; You-Lin Chen; Li-Jen Weng – Journal of Experimental Education, 2024
The second version of Kaiser's Measure of Sampling Adequacy (MSA[subscript 2]) has been widely applied to assess the factorability of data in psychological research. The MSA[subscript 2] is developed in the population and little is known about its behavior in finite samples. If estimated MSA[subscript 2]s are biased due to sampling errors,…
Descriptors: Error of Measurement, Reliability, Sampling, Statistical Bias
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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
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van Aert, Robbie C. M. – Research Synthesis Methods, 2023
The partial correlation coefficient (PCC) is used to quantify the linear relationship between two variables while taking into account/controlling for other variables. Researchers frequently synthesize PCCs in a meta-analysis, but two of the assumptions of the common equal-effect and random-effects meta-analysis model are by definition violated.…
Descriptors: Correlation, Meta Analysis, Sampling, Simulation
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Yunting Liu; Shreya Bhandari; Zachary A. Pardos – British Journal of Educational Technology, 2025
Effective educational measurement relies heavily on the curation of well-designed item pools. However, item calibration is time consuming and costly, requiring a sufficient number of respondents to estimate the psychometric properties of items. In this study, we explore the potential of six different large language models (LLMs; GPT-3.5, GPT-4,…
Descriptors: Artificial Intelligence, Test Items, Psychometrics, Educational Assessment
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Nuria Real-Brioso; Eduardo Estrada; Pablo F. Cáncer – Structural Equation Modeling: A Multidisciplinary Journal, 2024
Accelerated longitudinal designs (ALDs) provide an opportunity to capture long developmental periods in a shorter time framework using a relatively small number of assessments. Prior literature has investigated whether univariate developmental processes can be characterized with data obtained from ALDs. However, many important questions in…
Descriptors: Longitudinal Studies, Psychology, Cognitive Development, Brain Hemisphere Functions
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Domínguez Islas, Clara; Rice, Kenneth M. – Research Synthesis Methods, 2022
Bayesian methods seem a natural choice for combining sources of evidence in meta-analyses. However, in practice, their sensitivity to the choice of prior distribution is much less attractive, particularly for parameters describing heterogeneity. A recent non-Bayesian approach to fixed-effects meta-analysis provides novel ways to think about…
Descriptors: Bayesian Statistics, Evidence, Meta Analysis, Statistical Inference
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Bott, Franziska M.; Meiser, Thorsten – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2020
Pseudocontingencies are inferences of correlations between variables, like two options and two outcomes, drawn on the basis of their skewed base rates covarying across a third variable (e.g., two contexts). Here, we investigated the effect of pseudocontingency inference on choice behavior. When choices between two options are not based on the…
Descriptors: Inferences, Selection, Sampling, Correlation
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Stanley, T. D.; Doucouliagos, Hristos – Research Synthesis Methods, 2023
Partial correlation coefficients are often used as effect sizes in the meta-analysis and systematic review of multiple regression analysis research results. There are two well-known formulas for the variance and thereby for the standard error (SE) of partial correlation coefficients (PCC). One is considered the "correct" variance in the…
Descriptors: Correlation, Statistical Bias, Error Patterns, Error Correction
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Olanipekun, Oluwaseun L.; Zhao, JuLong; Wang, Rongdong; A. Sedory, Stephen; Singh, Sarjinder – Sociological Methods & Research, 2023
In carrying out surveys involving sensitive characteristics, randomized response models have been considered among the best techniques since they provide the maximum privacy protection to the respondents and procure honest responses. Over the years, researchers have carried out studies on the estimation of proportions of the population possessing…
Descriptors: Correlation, Smoking, Thinking Skills, Health Behavior
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Bom, Pedro R. D.; Rachinger, Heiko – Research Synthesis Methods, 2020
Meta-studies are often conducted on empirical findings obtained from overlapping samples. Sample overlap is common in research fields that strongly rely on aggregated observational data (eg, economics and finance), where the same set of data may be used in several studies. More generally, sample overlap tends to occur whenever multiple estimates…
Descriptors: Meta Analysis, Sampling, Research Problems, Computation
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Pere J. Ferrando; David Navarro-González; Fabia Morales-Vives – Educational and Psychological Measurement, 2025
The problem of local item dependencies (LIDs) is very common in personality and attitude measures, particularly in those that measure narrow-bandwidth dimensions. At the structural level, these dependencies can be modeled by using extended factor analytic (FA) solutions that include correlated residuals. However, the effects that LIDs have on the…
Descriptors: Scores, Accuracy, Evaluation Methods, Factor Analysis
Kelvin Terrell Pompey – ProQuest LLC, 2021
Many methods are used to measure interrater reliability for studies where each target receives ratings by a different set of judges. The purpose of this study is to explore the use of hierarchical modeling for estimating interrater reliability using the intraclass correlation coefficient. This study provides a description of how the ICC can be…
Descriptors: Interrater Reliability, Evaluation Methods, Test Reliability, Correlation
Kush, Joseph M.; Konold, Timothy R.; Bradshaw, Catherine P. – Grantee Submission, 2021
Multilevel structural equation (MSEM) models allow researchers to model latent factor structures at multiple levels simultaneously by decomposing within- and between-group variation. Yet the extent to which the sampling ratio (i.e., proportion of cases sampled from each group) influences the results of MSEM models remains unknown. This paper…
Descriptors: Sampling, Structural Equation Models, Factor Structure, Monte Carlo Methods
Lia E. Follet; Hide Okuno; Andres De Los Reyes – Grantee Submission, 2022
Socially anxious adolescents commonly experience impaired interpersonal functioning with unfamiliar, same-age peers. Yet, we lack short screening tools for assessing peer-related impairments. Recent work revealed that a parent-reported, three-item screening tool produced scores that uniquely related to social anxiety concerns. However, this tool…
Descriptors: Anxiety, Peer Influence, Early Adolescents, Parent Attitudes
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