Supplementary materials [code] to: A simulation-based scaled test statistic for assessing model-data fit in least-squares unrestricted factor-analysis solutions
Author(s) / Creator(s)
Lorenzo-Seva, Urbano
Ferrando, Pere J.
Abstract / Description
Supplementary materials [code] to: Lorenzo-Seva, U., & Ferrando, P. J. (2023). A simulation-based scaled test statistic for assessing model-data fit in least-squares unrestricted factor-analysis solutions. Methodology, 19(2). https://doi.org/10.5964/meth.9839
Keyword(s)
goodness-of-fit indices principal axis factoring MINRES ULS unrestricted factor analysis power analysis minimum rank factor analysis chi square test of fit statisticPersistent Identifier
Date of first publication
2023-06-26
Publisher
PsychOpen GOLD
Is referenced by
Citation
Lorenzo-Seva, U., & Ferrando, P. J. (2023). Supplementary materials [code] to: A simulation-based scaled test statistic for assessing model-data fit in least-squares unrestricted factor-analysis solutions [R code, data extraction scripts]. PsychOpen GOLD. https://doi.org/10.23668/psycharchives.12951
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Lorenzo-Seva_Ferrando_2023_LOSEFER_Model-data_fit_in_unrestricted_solutions_SUPPL_PrincipalAxes.rUnknown - 13.81KBMD5: d76a9be63a85f02c516f291e0939f250Description: Principal axes factor analysis code
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Lorenzo-Seva_Ferrando_2023_LOSEFER_Model-data_fit_in_unrestricted_solutions_SUPPL_PCA.rUnknown - 12.91KBMD5: 22ac82e958465d05087870c242c17a1bDescription: Principal component analysis code
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Lorenzo-Seva_Ferrando_2023_LOSEFER_Model-data_fit_in_unrestricted_solutions_SUPPL_Centroide.rUnknown - 12.79KBMD5: 3dfc482dc82b446fc7473ee603bd6ca8Description: Centroide code
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There are no other versions of this object.
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Author(s) / Creator(s)Lorenzo-Seva, Urbano
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Author(s) / Creator(s)Ferrando, Pere J.
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PsychArchives acquisition timestamp2023-06-26T11:35:04Z
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Made available on2023-06-26T11:35:04Z
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Date of first publication2023-06-26
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Abstract / DescriptionSupplementary materials [code] to: Lorenzo-Seva, U., & Ferrando, P. J. (2023). A simulation-based scaled test statistic for assessing model-data fit in least-squares unrestricted factor-analysis solutions. Methodology, 19(2). https://doi.org/10.5964/meth.9839en_US
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Publication statusunknownen_US
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Review statusunknownen_US
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Table of contentsThe supplementary materials provided are the R code and script for different data extraction methods in Lorenzo-Seva & Ferrando, (2023).en_US
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CitationLorenzo-Seva, U., & Ferrando, P. J. (2023). Supplementary materials [code] to: A simulation-based scaled test statistic for assessing model-data fit in least-squares unrestricted factor-analysis solutions [R code, data extraction scripts]. PsychOpen GOLD. https://doi.org/10.23668/psycharchives.12951en_US
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Persistent Identifierhttps://hdl.handle.net/20.500.12034/8454
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Persistent Identifierhttps://doi.org/10.23668/psycharchives.12951
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Language of contentengen_US
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PublisherPsychOpen GOLDen_US
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Is referenced byhttps://doi.org/10.5964/meth.9839
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Is related tohttps://www.psycharchives.org/handle/20.500.12034/8453
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Is related tohttps://hdl.handle.net/20.500.12034/9145
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Keyword(s)goodness-of-fit indicesen_US
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Keyword(s)principal axis factoringen_US
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Keyword(s)MINRESen_US
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Keyword(s)ULSen_US
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Keyword(s)unrestricted factor analysisen_US
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Keyword(s)power analysisen_US
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Keyword(s)minimum rank factor analysisen_US
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Keyword(s)chi square test of fit statisticen_US
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Dewey Decimal Classification number(s)150
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TitleSupplementary materials [code] to: A simulation-based scaled test statistic for assessing model-data fit in least-squares unrestricted factor-analysis solutionsen_US
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DRO typecodeen_US