A Modernized Heuristic Approach to Robust Exploratory Factor Analysis
Exploratory Factor Analysis (EFA) is a widely used approach for exploring latent traits. The EFA literature contains many inconsistencies regarding appropriate sample sizes, remedies for violation of assumptions, and the use of rotational methods. Given that EFA is an iterative process, which involv...
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| Autor*in: |
Gibson Jr., Terry O. [verfasserIn] Morrow, Jennifer Ann [verfasserIn] Rocconi, Louis M. [verfasserIn] |
|---|
| Format: |
E-Artikel |
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| Sprache: |
Englisch ; Französisch |
| Erschienen: |
2020 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
In: Tutorials in Quantitative Methods for Psychology - Université d'Ottawa, 2011, 16(2020), 4, Seite 295-307 |
|---|---|
| Übergeordnetes Werk: |
volume:16 ; year:2020 ; number:4 ; pages:295-307 |
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10.20982/tqmp.16.4.p295 |
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Exploratory Factor Analysis (EFA) is a widely used approach for exploring latent traits. The EFA literature contains many inconsistencies regarding appropriate sample sizes, remedies for violation of assumptions, and the use of rotational methods. Given that EFA is an iterative process, which involves varied decision-making, the objective of the current paper is to highlight the use of modernized methods using a heuristic approach for performing robust EFA to achieve optimal results. An example implementing these methods is presented using free online software (FACTOR). The paper concludes with seven recommendations for achieving well-defined factor solutions. |
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Exploratory Factor Analysis (EFA) is a widely used approach for exploring latent traits. The EFA literature contains many inconsistencies regarding appropriate sample sizes, remedies for violation of assumptions, and the use of rotational methods. Given that EFA is an iterative process, which involves varied decision-making, the objective of the current paper is to highlight the use of modernized methods using a heuristic approach for performing robust EFA to achieve optimal results. An example implementing these methods is presented using free online software (FACTOR). The paper concludes with seven recommendations for achieving well-defined factor solutions. |
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Exploratory Factor Analysis (EFA) is a widely used approach for exploring latent traits. The EFA literature contains many inconsistencies regarding appropriate sample sizes, remedies for violation of assumptions, and the use of rotational methods. Given that EFA is an iterative process, which involves varied decision-making, the objective of the current paper is to highlight the use of modernized methods using a heuristic approach for performing robust EFA to achieve optimal results. An example implementing these methods is presented using free online software (FACTOR). The paper concludes with seven recommendations for achieving well-defined factor solutions. |
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<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">DOAJ036074454</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230307224231.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">230227s2020 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.20982/tqmp.16.4.p295</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)DOAJ036074454</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)DOAJ414a4a83138343bca8cad35f03a38644</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield><subfield code="a">fre</subfield></datafield><datafield tag="050" ind1=" " ind2="0"><subfield code="a">BF1-990</subfield></datafield><datafield tag="100" ind1="0" ind2=" "><subfield code="a">Gibson Jr., Terry O.</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="2"><subfield code="a">A Modernized Heuristic Approach to Robust Exploratory Factor Analysis</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2020</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Exploratory Factor Analysis (EFA) is a widely used approach for exploring latent traits. 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