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Rotation to Simple Loadings Using Component Loss Functions: The Oblique Case

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  • Robert Jennrich

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  • Robert Jennrich, 2006. "Rotation to Simple Loadings Using Component Loss Functions: The Oblique Case," Psychometrika, Springer;The Psychometric Society, vol. 71(1), pages 173-191, March.
    • Handle: RePEc:spr:psycho:v:71:y:2006:i:1:p:173-191
    DOI: 10.1007/s11336-003-1136-B
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    References listed on IDEAS

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    1. Henk Kiers, 1994. "Simplimax: Oblique rotation to an optimal target with simple structure," Psychometrika, Springer;The Psychometric Society, vol. 59(4), pages 567-579, December.
    2. Henry Kaiser, 1958. "The varimax criterion for analytic rotation in factor analysis," Psychometrika, Springer;The Psychometric Society, vol. 23(3), pages 187-200, September.
    3. Edward Cureton & Stanley Mulaik, 1975. "The weighted varimax rotation and the promax rotation," Psychometrika, Springer;The Psychometric Society, vol. 40(2), pages 183-195, June.
    4. Robert Jennrich, 2004. "Derivative free gradient projection algorithms for rotation," Psychometrika, Springer;The Psychometric Society, vol. 69(3), pages 475-480, September.
    5. repec:ucp:bkecon:9780226316529 is not listed on IDEAS
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    Cited by:

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    2. Simon Freyaldenhoven, 2020. "Identification Through Sparsity in Factor Models," Working Papers 20-25, Federal Reserve Bank of Philadelphia.
    3. Liu, Xinyi Lin & Wallin, Gabriel & Chen, Yunxiao & Moustaki, Irini, 2023. "Rotation to sparse loadings using Lp losses and related inference problems," LSE Research Online Documents on Economics 118349, London School of Economics and Political Science, LSE Library.
    4. Conti, Gabriella & Frühwirth-Schnatter, Sylvia & Heckman, James J. & Piatek, Rémi, 2014. "Bayesian exploratory factor analysis," Journal of Econometrics, Elsevier, vol. 183(1), pages 31-57.
    5. Kawano, Shuichi & Fujisawa, Hironori & Takada, Toyoyuki & Shiroishi, Toshihiko, 2015. "Sparse principal component regression with adaptive loading," Computational Statistics & Data Analysis, Elsevier, vol. 89(C), pages 192-203.
    6. Rosember Guerra-Urzola & Katrijn Van Deun & Juan C. Vera & Klaas Sijtsma, 2021. "A Guide for Sparse PCA: Model Comparison and Applications," Psychometrika, Springer;The Psychometric Society, vol. 86(4), pages 893-919, December.
    7. James Heckman & Rodrigo Pinto & Peter Savelyev, 2013. "Understanding the Mechanisms through Which an Influential Early Childhood Program Boosted Adult Outcomes," American Economic Review, American Economic Association, vol. 103(6), pages 2052-2086, October.
    8. Kawano, Shuichi & Fujisawa, Hironori & Takada, Toyoyuki & Shiroishi, Toshihiko, 2018. "Sparse principal component regression for generalized linear models," Computational Statistics & Data Analysis, Elsevier, vol. 124(C), pages 180-196.
    9. Eldad Davidov & Bengt Muthen & Peter Schmidt, 2018. "Measurement Invariance in Cross-National Studies," Sociological Methods & Research, , vol. 47(4), pages 631-636, November.
    10. Jin, Shaobo & Moustaki, Irini & Yang-Wallentin, Fan, 2018. "Approximated penalized maximum likelihood for exploratory factor analysis: an orthogonal case," LSE Research Online Documents on Economics 88118, London School of Economics and Political Science, LSE Library.
    11. Almudena Recio-Román & Manuel Recio-Menéndez & María Victoría Román-González, 2021. "Vaccine Hesitancy and Political Populism. An Invariant Cross-European Perspective," IJERPH, MDPI, vol. 18(24), pages 1-20, December.
    12. Shaobo Jin & Irini Moustaki & Fan Yang-Wallentin, 2018. "Approximated Penalized Maximum Likelihood for Exploratory Factor Analysis: An Orthogonal Case," Psychometrika, Springer;The Psychometric Society, vol. 83(3), pages 628-649, September.
    13. Xinyi Liu & Gabriel Wallin & Yunxiao Chen & Irini Moustaki, 2023. "Rotation to Sparse Loadings Using $$L^p$$ L p Losses and Related Inference Problems," Psychometrika, Springer;The Psychometric Society, vol. 88(2), pages 527-553, June.
    14. Ofer Mintz & Imran S Currim & Jan-Benedict E M Steenkamp & Martijn Jong, 2021. "Managerial metric use in marketing decisions across 16 countries: A cultural perspective," Journal of International Business Studies, Palgrave Macmillan;Academy of International Business, vol. 52(8), pages 1474-1500, October.
    15. Guerra Urzola, Rosember & Van Deun, Katrijn & Vera, J. C. & Sijtsma, K., 2021. "A guide for sparse PCA : Model comparison and applications," Other publications TiSEM 4d35b931-7f49-444b-b92f-a, Tilburg University, School of Economics and Management.
    16. Bengt Muthén & Tihomir Asparouhov, 2018. "Recent Methods for the Study of Measurement Invariance With Many Groups," Sociological Methods & Research, , vol. 47(4), pages 637-664, November.
    17. Shuichi Kawano, 2021. "Sparse principal component regression via singular value decomposition approach," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 15(3), pages 795-823, September.
    18. Nickolay Trendafilov & Kohei Adachi, 2015. "Sparse Versus Simple Structure Loadings," Psychometrika, Springer;The Psychometric Society, vol. 80(3), pages 776-790, September.

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