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Estimating the Root Mean Square Error of Approximation (RMSEA) with Multiply Imputed Data Under Non-Normality

Datos Bibliográficos

ID12424919
AutoresYunhang Yin (University of South Carolina), Amanda J Fairchild (0000-0001-8668-4658, University of South Carolina), Dexin Shi (0000-0002-4120-6756, University of South Carolina), Taehun Lee (0000-0001-8261-701X, Korea University)
Año2025
Volumen32
Número5
Páginas832-857
Fecha de publicación2025-07-21
Peer ReviewedSí
Open AccessNo
TipoARTICLE
RevistaStructural Equation Modeling: A Multidisciplinary Journal (JOURNAL)
Identificadores de la revistaISSN: 1070-5511 • E-ISSN: 1532-8007
EditorialTaylor & Francis (PUBLISHER • GB)
DOI10.1080/10705511.2025.2515229
OpenAlexW4412531179
IdiomaEN
Citas recibidas1
Referencias citadas93

Econometrics · Mean squared error · Normality · Root mean square · Statistics · Structural equation modeling · Control Systems and Identification · Engineering · Mathematics · Statistical and numerical algorithms · Statistical Methods and Inference · Applied Mathematics

  • Estimating RMSEA D (and Associated Confidence Intervals) Under Non-Normality

    Yunhang Yin, Dexin Shi et al.•Structural Equation Modeling: A…•2025

  • Analysis of Incomplete Multivariate Data

    Joseph L Schafer•Analysis of Incomplete…•1997

  • Flexible Imputation of Missing Data, Second Edition

    Stef Van Buuren•Flexible Imputation of Missing…•2018

  • The impact of nonnormality on full information maximum-likelihood estimation for structural equation models with missing data.

    Craig K Enders•Psychological Methods•2001

  • Testing Structural Equation Models or Detection of Misspecifications?

    Willem E Saris, Albert Satorra et al.•Structural Equation Modeling: A…•2009

  • A comparison of inclusive and restrictive strategies in modern missing data procedures.

    Linda M Collins, Joseph L Schafer et al.•Psychological Methods•2001

  • Reporting practices in confirmatory factor analysis

    Dennis L Jackson, J Arthur Gillaspy et al.•Psychological Methods•2009

  • Amelia II

    Open Access•James Honaker, Gary King et al.•Journal of Statistical Software•2011

  • Robustness in the Strategy of Scientific Model Building

    Open Access•George E P Box•Robustness in statistics•1979

  • Maximum Likelihood Estimation of Structural Equation Models for Continuous Data

    Alberto Maydeu-Olivares, Alberto Maydeu‐olivare•Structural Equation Modeling: A…•2017

  • Missing Data Techniques for Structural Equation Modeling.

    P D Allison•Journal of Abnormal Psychology•2003

  • Structural equation modelling

    Open Access•Paul Barrett•Personality and Individual…•2007

  • Simulation Study on Fit Indexes in CFA Based on Data With Slightly Distorted Simple Structure

    André Beauducel, Werner W Wittmann•Structural Equation Modeling: A…•2005

  • A comparison of full information maximum likelihood and multiple imputation in structural equation modeling with missing data.

    Taehun Lee, Dexin Shi•Psychological Methods•2021

  • Attrition in developmental psychology

    Open Access•Jody S Nicholson, Pascal R Deboeck et al.•International Journal of…•2017

  • Simulating Multivariate Nonnormal Distributions

    Open Access•C David Vale, Vincent A Maurelli•Psychometrika•1983

  • Missing Data in Educational Research

    Open Access•James L Peugh, Craig K Enders•Review of Educational Research•2004

  • Inference and missing data

    Donald B Rubin•Biometrika•1976

  • Cutoff criteria for fit indexes in covariance structure analysis

    Li‐tze Hu, Peter M Bentler•Structural Equation Modeling: A…•1999

  • Mice

    Open Access•Stef Van Buuren, Karin Groothuis‐Oudshoorn et al.•Journal of Statistical Software•2011

  • The robustness of test statistics to nonnormality and specification error in confirmatory factor analysis.

    Patrick J Curran, Stephen G West et al.•Psychological Methods•1996

  • Testing Structural Equation Models

    J Scott Long, Kenneth A Bollen•Testing Structural Equation Models•2012

  • Asymptotic is Better than Bollen-Stine Bootstrapping to Assess Model Fit

    Raul C Ferraz, Alberto Maydeu‐olivare et al.•Structural Equation Modeling: A…•2022

  • Effects of Multivariate Non-Normality and Missing Data on the Root Mean Square Error of Approximation

    Lisa J Jobst, Christoph Heine et al.•Structural Equation Modeling: A…•2021

  • The Effect of Model Size on the Root Mean Square Error of Approximation (RMSEA)

    Yunhang Yin, Dexin Shi et al.•Structural Equation Modeling: A…•2023

  • Correct Estimation Methods for RMSEA Under Missing Data

    Keke Lai•Structural Equation Modeling: A…•2021

  • Computational Options for Standard Errors and Test Statistics with Incomplete Normal and Nonnormal Data in SEM

    Open Access•Victoria Savalei, Yves Rosseel•Structural Equation Modeling: A…•2022

  • Fitting latent growth models with small sample sizes and non-normal missing data

    Open Access•Dexin Shi, Christine Distefano et al.•International Journal of…•2021

  • Fitting Ordinal Factor Analysis Models With Missing Data

    Open Access•Dexin Shi, Taehun Lee et al.•Educational and Psychological…•2020

  • Understanding the Model Size Effect on SEM Fit Indices

    Open Access•Dexin Shi, Taehun Lee et al.•Educational and Psychological…•2019

  • Evaluating Model Fit of Measurement Models in Confirmatory Factor Analysis

    Open Access•David Goretzko, Karik Siemund et al.•Educational and Psychological…•2024

  • Evaluating Close Fit in Ordinal Factor Analysis Models With Multiply Imputed Data

    Open Access•Dexin Shi, Bo Zhang et al.•Educational and Psychological…•2024

  • Multiple Imputation for Nonresponse in Surveys

    Open Access•Donald B Rubin•Multiple Imputation for…•1987

  • Statistical Matching Using File Concatenation With Adjusted Weights and Multiple Imputations

    Donald B Rubin•Journal of Business and Economic…•1986

  • Missing-Data Adjustments in Large Surveys

    Roderick J A Little, Roderick J Little•Journal of Business and Economic…•1988

  • Accuracy in Parameter Estimation for the Root Mean Square Error of Approximation

    Ken Kelley, Keke Lai•Multivariate Behavioral Research•2011

  • Choosing the Optimal Number of Factors in Exploratory Factor Analysis

    Kristopher J Preacher, Guangjian Zhang et al.•Multivariate Behavioral Research•2013

  • A Simple Simulation Technique for Nonnormal Data with Prespecified Skewness, Kurtosis, and Covariance Matrix

    Njål Foldnes, Ulf Olsson et al.•Multivariate Behavioral Research•2016

  • Adjusting Incremental Fit Indices for Nonnormality

    Patricia E Brosseau-Liard, Victoria Savalei•Multivariate Behavioral Research•2014

  • The Relationship Between the Standardized Root Mean Square Residual and Model Misspecification in Factor Analysis Models

    Dexin Shi, Alberto Maydeu‐olivare et al.•Multivariate Behavioral Research•2018

  • Presidential Address

    Robert C Maccallum•Multivariate Behavioral Research•2003

  • On the Computation of the RMSEA and CFI from the Mean-And-Variance Corrected Test Statistic with Nonnormal Data in SEM

    Victoria Savalei•Multivariate Behavioral Research•2018

  • Investigating the Effect of Missing Data on the Population CFI and RMSEA values

    Xijuan Zhang, Victoria Savalei•Multivariate Behavioral Research•2018

  • Structural Model Evaluation and Modification

    James H Steiger•Multivariate Behavioral Research•1990

  • Structural Equation Modeling in Organizational Research

    Open Access•Michael J Zyphur, Cavan V Bonner et al.•Annual Review of Organizational…•2022

  • Univariate and multivariate skewness and kurtosis for measuring nonnormality

    Open Access•Meghan K Cain, Zhiyong Zhang et al.•Behavior Research Methods•2016

  • Estimation of Linear Models with Incomplete Data

    P D Allison•Sociological Methodology•1987

  • Use of missing data methods in longitudinal studies

    Helena Jeličić, Erin Phelps et al.•Developmental Psychology•2009

  • The unicorn, the normal curve, and other improbable creatures

    Theodore Micceri•Psychological Bulletin•1989

  • Alternative Ways of Assessing Model Fit

    Open Access•Michael W Browne, Robert Cudeck•Sociological Methods & Research•1992

Obras citantes distintas1
Citas por año1
Intervalo de citas2025 - 2025 (1)
Velocidad de citaciónrecent
Altamente citadoNo
Tipos de citaNeutras: 1
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