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Asymptotic comparison of missing data procedures for estimating factor loadings

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  • C. Hendricks Brown

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  • C. Hendricks Brown, 1983. "Asymptotic comparison of missing data procedures for estimating factor loadings," Psychometrika, Springer;The Psychometric Society, vol. 48(2), pages 269-291, June.
    • Handle: RePEc:spr:psycho:v:48:y:1983:i:2:p:269-291
    DOI: 10.1007/BF02294022
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    References listed on IDEAS

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    1. Neil Timm, 1970. "The estimation of variance-covariance and correlation matrices from incomplete data," Psychometrika, Springer;The Psychometric Society, vol. 35(4), pages 417-437, December.
    2. Terry Gleason & Richard Staelin, 1975. "A proposal for handling missing data," Psychometrika, Springer;The Psychometric Society, vol. 40(2), pages 229-252, June.
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    Citations

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    Cited by:

    1. Tang, Man-Lai & Bentler, Peter M., 1998. "Theory and method for constrained estimation in structural equation models with incomplete data," Computational Statistics & Data Analysis, Elsevier, vol. 27(3), pages 257-270, May.
    2. Michel Rousseau & Marielle Simon & Richard Bertrand & Krystal Hachey, 2012. "Reporting missing data: a study of selected articles published from 2003–2007," Quality & Quantity: International Journal of Methodology, Springer, vol. 46(5), pages 1393-1406, August.
    3. Barnes, Stuart J. & Vidgen, Richard T., 2014. "Technology socialness and Web site satisfaction," Technological Forecasting and Social Change, Elsevier, vol. 89(C), pages 12-25.
    4. Ting Lin, 2010. "A comparison of multiple imputation with EM algorithm and MCMC method for quality of life missing data," Quality & Quantity: International Journal of Methodology, Springer, vol. 44(2), pages 277-287, February.
    5. Bengt Muthén & David Kaplan & Michael Hollis, 1987. "On structural equation modeling with data that are not missing completely at random," Psychometrika, Springer;The Psychometric Society, vol. 52(3), pages 431-462, September.
    6. Olinsky, Alan & Chen, Shaw & Harlow, Lisa, 2003. "The comparative efficacy of imputation methods for missing data in structural equation modeling," European Journal of Operational Research, Elsevier, vol. 151(1), pages 53-79, November.
    7. Ke-Hai Yuan & Linda Marshall & Peter Bentler, 2002. "A unified approach to exploratory factor analysis with missing data, nonnormal data, and in the presence of outliers," Psychometrika, Springer;The Psychometric Society, vol. 67(1), pages 95-121, March.
    8. Tang, Man-Lai & Lee, Sik-Yum, 1998. "Analysis of structural equation models with censored or truncated data via EM algorithm," Computational Statistics & Data Analysis, Elsevier, vol. 27(1), pages 33-46, March.
    9. Hang Thi Thanh Vu & Jeonghan Ko, 2022. "Integrated Inventory Transshipment and Missing-Data Treatment Using Improved Imputation-Level Adjustment for Efficient Cross-Filling," Sustainability, MDPI, vol. 14(19), pages 1-24, October.
    10. Yuan, Ke-Hai, 2009. "Normal distribution based pseudo ML for missing data: With applications to mean and covariance structure analysis," Journal of Multivariate Analysis, Elsevier, vol. 100(9), pages 1900-1918, October.

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    Keywords

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