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Can We Differentiate a Latent Growth Curve Model from Competitors? Evidence Based on Individual Case Residuals
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Dan Wei; Peida Zhan; Hongyun Liu – Structural Equation Modeling: A Multidisciplinary Journal, 2024
In latent growth curve modeling (LGCM), overall fit indices have garnered increased disputation for model selection, and model fit evaluation based on the mean structure has becoming popularity. The present study developed a versatile fit index, named Weighted Root Mean Squared Errors (WRMSE), based on individual case residuals (ICRs) with the aim…
Descriptors: Structural Equation Models, Goodness of Fit, Error of Measurement, Computation
The Sensitivity of Bayesian Fit Indices to Structural Misspecification in Structural Equation Modeling
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Chunhua Cao; Benjamin Lugu; Jujia Li – Structural Equation Modeling: A Multidisciplinary Journal, 2024
This study examined the false positive (FP) rates and sensitivity of Bayesian fit indices to structural misspecification in Bayesian structural equation modeling. The impact of measurement quality, sample size, model size, the magnitude of misspecified path effect, and the choice or prior on the performance of the fit indices was also…
Descriptors: Structural Equation Models, Bayesian Statistics, Measurement, Error of Measurement
A Critical Evaluation of the P-Factor Literature. Perspective
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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
Evaluating Methods for Assessing Model Fit in Diagnostic Classification Models
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W. Jake Thompson – Grantee Submission, 2024
Diagnostic classification models (DCMs) are psychometric models that can be used to estimate the presence or absence of psychological traits, or proficiency on fine-grained skills. Critical to the use of any psychometric model in practice, including DCMs, is an evaluation of model fit. Traditionally, DCMs have been estimated with maximum…
Descriptors: Bayesian Statistics, Classification, Psychometrics, Goodness of Fit
Making the Cut: Comparing Methods for Selecting Cut-Point Location in Logistic Regression
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Weiss, Brandi A.; Dardick, William – Journal of Experimental Education, 2021
Classification measures and entropy variants can be used as indicators of model fit for logistic regression. These measures rely on a cut-point, "c," to determine predicted group membership. While recommendations exist for determining the location of the cut-point, these methods are primarily anecdotal. The current study used Monte Carlo…
Descriptors: Cutting Scores, Regression (Statistics), Classification, Monte Carlo Methods
Evaluation of the Goodness-of-Fit Index M[subscript ord] in Polytomous DCMS with Hierarchical Attribute Structures
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Haimiao Yuan – ProQuest LLC, 2022
The application of diagnostic classification models (DCMs) in the field of educational measurement is getting more attention in recent years. To make a valid inference from the model, it is important to ensure that the model fits the data. The purpose of the present study was to investigate the performance of the limited information…
Descriptors: Goodness of Fit, Educational Assessment, Educational Diagnosis, Models
Separating the Odds: Thresholds for Entropy in Logistic Regression
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Weiss, Brandi A.; Dardick, William – Journal of Experimental Education, 2020
Researchers are often reluctant to rely on classification rates because a model with favorable classification rates but poor separation may not replicate well. In comparison, entropy captures information about borderline cases unlikely to generalize to the population. In logistic regression, the correctness of predicted group membership is known,…
Descriptors: Classification, Regression (Statistics), Goodness of Fit, Monte Carlo Methods
Fitting Large Factor Analysis Models with Ordinal Data
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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
Preschool Psychopathology Reported by Parents in 23 Societies: Testing the Seven-Syndrome Model of the Child Behavior Checklist for Ages 1.5-5
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Ivanova, Masha Y.; Achenbach, Thomas M.; Rescorla, Leslie A.; Harder, Valerie S.; Ang, Rebecca P.; Bilenberg, Niels; Bjarnadottir, Gudrun; Capron, Christiane; De Pauw, Sarah S. W.; Dias, Pedro; Dobrean, Anca; Doepfner, Manfred; Duyme, Michele; Eapen, Valsamma; Erol, Nese; Esmaeili, Elaheh Mohammad; Ezpeleta, Lourdes; Frigerio, Alessandra; Goncalves, Miguel M.; Gudmundsson, Halldor S.; Jeng, Suh-Fang; Jetishi, Pranvera; Jusiene, Roma; Kim, Young-Ah; Kristensen, Solvejg; Lecannelier, Felipe; Leung, Patrick W. L.; Liu, Jianghong; Montirosso, Rosario; Oh, Kyung Ja; Plueck, Julia; Pomalima, Rolando; Shahini, Mimoza; Silva, Jaime R.; Simsek, Zynep; Sourander, Andre; Valverde, Jose; Van Leeuwen, Karla G.; Woo, Bernardine S. C.; Wu, Yen-Tzu; Zubrick, Stephen R.; Verhulst, Frank C. – Journal of the American Academy of Child & Adolescent Psychiatry, 2010
Objective: To test the fit of a seven-syndrome model to ratings of preschoolers' problems by parents in very diverse societies. Method: Parents of 19,106 children 18 to 71 months of age from 23 societies in Asia, Australasia, Europe, the Middle East, and South America completed the Child Behavior Checklist for Ages 1.5-5 (CBCL/1.5-5). Confirmatory…
Descriptors: Check Lists, Social Problems, Psychopathology, Child Behavior
Is Parceling Really Necessary? A Comparison of Results from Item Parceling and Categorical Variable Methodology
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Bandalos, Deborah L. – Structural Equation Modeling: A Multidisciplinary Journal, 2008
This study examined the efficacy of 4 different parceling methods for modeling categorical data with 2, 3, and 4 categories and with normal, moderately nonnormal, and severely nonnormal distributions. The parceling methods investigated were isolated parceling in which items were parceled with other items sharing the same source of variance, and…
Descriptors: Structural Equation Models, Computation, Goodness of Fit, Classification
The Impact of Categorization with Confirmatory Factor Analysis.
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DiStefano, Christine – Structural Equation Modeling, 2002
Investigated the impact of categorization on confirmatory factor analysis parameter estimates, standard errors, and five ad hoc fit indexes through simulation studies. Results replicate some previous studies but also suggest that tests of parameter estimates will be underestimated and the amount of underestimation will increase as saturation…
Descriptors: Classification, Error of Measurement, Estimation (Mathematics), Goodness of Fit
Conditional Standard Errors, Reliability and Decision Consistency of Performance Levels Using Polytomous IRT.
Wang, Tianyou; And Others – 1996
M. J. Kolen, B. A. Hanson, and R. L. Brennan (1992) presented a procedure for assessing the conditional standard error of measurement (CSEM) of scale scores using a strong true-score model. They also investigated the ways of using nonlinear transformation from number-correct raw score to scale score to equalize the conditional standard error along…
Descriptors: Ability, Classification, Error of Measurement, Goodness of Fit
Rasch Analysis Using SPSS.
Phillips, Gary W. – 1983
Ways in which the Statistical Package for the Social Sciences (SPSS) can be used to perform some Rasch analyses are described in detail. It is shown how SPSS and a set of item calibrations can be used to estimate person abilities, standard errors of measurement, test characteristic curve, test information curve, classification consistency on a…
Descriptors: Classification, Computer Software, Error of Measurement, Estimation (Mathematics)
Improving Prediction by Correcting Test Scores for Person Disturbances Using the Rasch Model.
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Westfall, Philip Jean-Louis; D'Costa, Ayres G. – 1987
This study, based on the Rasch model, used R. M. Smith's (1986) classification of measurement disturbances to assess the Rasch model approach to error control and statistical prediction. Partitioning the error component into a person component, an item-person interaction component, and a random unexplained error component has the net effect of…
Descriptors: Classification, College Entrance Examinations, Error of Measurement, French