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Ashley L. Watts; Ashley L. Greene; Wes Bonifay; Eiko L. Fried – Grantee Submission, 2023
The p-factor is a construct that is thought to explain and maybe even cause variation in all forms of psychopathology. Since its 'discovery' in 2012, hundreds of studies have been dedicated to the extraction and validation of statistical instantiations of the p-factor, called general factors of psychopathology. In this Perspective, we outline five…
Descriptors: Causal Models, Psychopathology, Goodness of Fit, Validity
Yuanfang Liu; Mark H. C. Lai; Ben Kelcey – Structural Equation Modeling: A Multidisciplinary Journal, 2024
Measurement invariance holds when a latent construct is measured in the same way across different levels of background variables (continuous or categorical) while controlling for the true value of that construct. Using Monte Carlo simulation, this paper compares the multiple indicators, multiple causes (MIMIC) model and MIMIC-interaction to a…
Descriptors: Classification, Accuracy, Error of Measurement, Correlation
Liu, Yixing; Thompson, Marilyn S. – Journal of Experimental Education, 2022
A simulation study was conducted to explore the impact of differential item functioning (DIF) on general factor difference estimation for bifactor, ordinal data. Common analysis misspecifications in which the generated bifactor data with DIF were fitted using models with equality constraints on noninvariant item parameters were compared under data…
Descriptors: Comparative Analysis, Item Analysis, Sample Size, Error of Measurement
DiStefano, Christine; McDaniel, Heather L.; Zhang, Liyun; Shi, Dexin; Jiang, Zhehan – Educational and Psychological Measurement, 2019
A simulation study was conducted to investigate the model size effect when confirmatory factor analysis (CFA) models include many ordinal items. CFA models including between 15 and 120 ordinal items were analyzed with mean- and variance-adjusted weighted least squares to determine how varying sample size, number of ordered categories, and…
Descriptors: Factor Analysis, Effect Size, Data, Sample Size
He, Qingping; Anwyll, Steve; Glanville, Matthew; Opposs, Dennis – Research Papers in Education, 2014
Since 2010, the whole national cohort Key Stage 2 (KS2) National Curriculum test in science in England has been replaced with a sampling test taken by pupils at the age of 11 from a nationally representative sample of schools annually. The study reported in this paper compares the performance of different subgroups of the samples (classified by…
Descriptors: National Curriculum, Sampling, Foreign Countries, Factor Analysis
Marsh, Herbert W.; Muthen, Bengt; Asparouhov, Tihomir; Ludtke, Oliver; Robitzsch, Alexander; Morin, Alexandre J. S.; Trautwein, Ulrich – Structural Equation Modeling: A Multidisciplinary Journal, 2009
This study is a methodological-substantive synergy, demonstrating the power and flexibility of exploratory structural equation modeling (ESEM) methods that integrate confirmatory and exploratory factor analyses (CFA and EFA), as applied to substantively important questions based on multidimentional students' evaluations of university teaching…
Descriptors: Feedback (Response), Class Size, Structural Equation Models, Construct Validity