Augmenting the Correlated Trait-Correlated Method Model for Multitrait-Multimethod Data
We introduce an approach for ensuring empirical identification of the correlated trait-correlated method (CT-CM) model under a variety of conditions. A set of models are referred to as augmented correlated trait-correlated method (ACT-CM) models because they are based on systematically augmenting th...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Castro-Schilo, Laura [verfasserIn] |
|---|
| Format: |
Artikel |
|---|---|
| Sprache: |
Englisch |
| Erschienen: |
2016 |
|---|
| Rechteinformationen: |
Nutzungsrecht: Copyright © Taylor & Francis Group, LLC |
|---|
| Schlagwörter: |
|---|
| Übergeordnetes Werk: |
Enthalten in: Structural equation modeling - Philadelphia, Pa. : Psychology Press, Taylor & Francis Group, 1994, 23(2016), 6, Seite 798 |
|---|---|
| Übergeordnetes Werk: |
volume:23 ; year:2016 ; number:6 ; pages:798 |
| Links: |
|---|
| DOI / URN: |
10.1080/10705511.2016.1214919 |
|---|
| Katalog-ID: |
OLC1986057542 |
|---|
| LEADER | 01000caa a2200265 4500 | ||
|---|---|---|---|
| 001 | OLC1986057542 | ||
| 003 | DE-627 | ||
| 005 | 20220215121158.0 | ||
| 007 | tu | ||
| 008 | 161202s2016 xx ||||| 00| ||eng c | ||
| 024 | 7 | |a 10.1080/10705511.2016.1214919 |2 doi | |
| 028 | 5 | 2 | |a PQ20161201 |
| 035 | |a (DE-627)OLC1986057542 | ||
| 035 | |a (DE-599)GBVOLC1986057542 | ||
| 035 | |a (PRQ)i1443-3497908e07841ced838373adb9cdce20af9910de3452e49e1ea1023b423256800 | ||
| 035 | |a (KEY)0238167220160000023000600798augmentingthecorrelatedtraitcorrelatedmethodmodelf | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
| 041 | |a eng | ||
| 082 | 0 | 4 | |a 300 |q DE-600 |
| 084 | |a 31.00 |2 bkl | ||
| 100 | 1 | |a Castro-Schilo, Laura |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Augmenting the Correlated Trait-Correlated Method Model for Multitrait-Multimethod Data |
| 264 | 1 | |c 2016 | |
| 336 | |a Text |b txt |2 rdacontent | ||
| 337 | |a ohne Hilfsmittel zu benutzen |b n |2 rdamedia | ||
| 338 | |a Band |b nc |2 rdacarrier | ||
| 520 | |a We introduce an approach for ensuring empirical identification of the correlated trait-correlated method (CT-CM) model under a variety of conditions. A set of models are referred to as augmented correlated trait-correlated method (ACT-CM) models because they are based on systematically augmenting the multitrait-multimethod matrix put forth by Campbell and Fiske (1959). We show results from a Monte Carlo simulation study in which data characteristics lead to an empirically underidentified standard CT-CM model, but a well-identified fully augmented correlated trait-correlated method (FACT-CM) model. This improved identification occurs even for a model in which equality constraints are imposed on loadings on each trait factor and loadings on each method factor-a specific case shown to lead to an empirically underidentified CT-CM model. | ||
| 540 | |a Nutzungsrecht: Copyright © Taylor & Francis Group, LLC | ||
| 650 | 4 | |a construct validity | |
| 650 | 4 | |a multitrait-multimethod models | |
| 650 | 4 | |a correlated trait-correlated method model | |
| 650 | 4 | |a method variance | |
| 650 | 4 | |a method effects | |
| 650 | 4 | |a Monte Carlo simulation | |
| 650 | 4 | |a Mathematical models | |
| 700 | 1 | |a Grimm, Kevin J |4 oth | |
| 700 | 1 | |a Widaman, Keith F |4 oth | |
| 773 | 0 | 8 | |i Enthalten in |t Structural equation modeling |d Philadelphia, Pa. : Psychology Press, Taylor & Francis Group, 1994 |g 23(2016), 6, Seite 798 |w (DE-627)188644075 |w (DE-600)1285122-X |w (DE-576)049955675 |x 1070-5511 |7 nnns |
| 773 | 1 | 8 | |g volume:23 |g year:2016 |g number:6 |g pages:798 |
| 856 | 4 | 1 | |u http://dx.doi.org/10.1080/10705511.2016.1214919 |3 Volltext |
| 856 | 4 | 2 | |u http://www.tandfonline.com/doi/abs/10.1080/10705511.2016.1214919 |
| 856 | 4 | 2 | |u http://search.proquest.com/docview/1829807528 |
| 912 | |a GBV_USEFLAG_A | ||
| 912 | |a SYSFLAG_A | ||
| 912 | |a GBV_OLC | ||
| 912 | |a SSG-OLC-MAT | ||
| 912 | |a GBV_ILN_70 | ||
| 912 | |a GBV_ILN_4012 | ||
| 936 | b | k | |a 31.00 |q AVZ |
| 951 | |a AR | ||
| 952 | |d 23 |j 2016 |e 6 |h 798 | ||
| author_variant |
l c s lcs |
|---|---|
| matchkey_str |
article:10705511:2016----::umnighcreaetatorltdehdoefrut |
| hierarchy_sort_str |
2016 |
| bklnumber |
31.00 |
| publishDate |
2016 |
| allfields |
10.1080/10705511.2016.1214919 doi PQ20161201 (DE-627)OLC1986057542 (DE-599)GBVOLC1986057542 (PRQ)i1443-3497908e07841ced838373adb9cdce20af9910de3452e49e1ea1023b423256800 (KEY)0238167220160000023000600798augmentingthecorrelatedtraitcorrelatedmethodmodelf DE-627 ger DE-627 rakwb eng 300 DE-600 31.00 bkl Castro-Schilo, Laura verfasserin aut Augmenting the Correlated Trait-Correlated Method Model for Multitrait-Multimethod Data 2016 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier We introduce an approach for ensuring empirical identification of the correlated trait-correlated method (CT-CM) model under a variety of conditions. A set of models are referred to as augmented correlated trait-correlated method (ACT-CM) models because they are based on systematically augmenting the multitrait-multimethod matrix put forth by Campbell and Fiske (1959). We show results from a Monte Carlo simulation study in which data characteristics lead to an empirically underidentified standard CT-CM model, but a well-identified fully augmented correlated trait-correlated method (FACT-CM) model. This improved identification occurs even for a model in which equality constraints are imposed on loadings on each trait factor and loadings on each method factor-a specific case shown to lead to an empirically underidentified CT-CM model. Nutzungsrecht: Copyright © Taylor & Francis Group, LLC construct validity multitrait-multimethod models correlated trait-correlated method model method variance method effects Monte Carlo simulation Mathematical models Grimm, Kevin J oth Widaman, Keith F oth Enthalten in Structural equation modeling Philadelphia, Pa. : Psychology Press, Taylor & Francis Group, 1994 23(2016), 6, Seite 798 (DE-627)188644075 (DE-600)1285122-X (DE-576)049955675 1070-5511 nnns volume:23 year:2016 number:6 pages:798 http://dx.doi.org/10.1080/10705511.2016.1214919 Volltext http://www.tandfonline.com/doi/abs/10.1080/10705511.2016.1214919 http://search.proquest.com/docview/1829807528 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT GBV_ILN_70 GBV_ILN_4012 31.00 AVZ AR 23 2016 6 798 |
| spelling |
10.1080/10705511.2016.1214919 doi PQ20161201 (DE-627)OLC1986057542 (DE-599)GBVOLC1986057542 (PRQ)i1443-3497908e07841ced838373adb9cdce20af9910de3452e49e1ea1023b423256800 (KEY)0238167220160000023000600798augmentingthecorrelatedtraitcorrelatedmethodmodelf DE-627 ger DE-627 rakwb eng 300 DE-600 31.00 bkl Castro-Schilo, Laura verfasserin aut Augmenting the Correlated Trait-Correlated Method Model for Multitrait-Multimethod Data 2016 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier We introduce an approach for ensuring empirical identification of the correlated trait-correlated method (CT-CM) model under a variety of conditions. A set of models are referred to as augmented correlated trait-correlated method (ACT-CM) models because they are based on systematically augmenting the multitrait-multimethod matrix put forth by Campbell and Fiske (1959). We show results from a Monte Carlo simulation study in which data characteristics lead to an empirically underidentified standard CT-CM model, but a well-identified fully augmented correlated trait-correlated method (FACT-CM) model. This improved identification occurs even for a model in which equality constraints are imposed on loadings on each trait factor and loadings on each method factor-a specific case shown to lead to an empirically underidentified CT-CM model. Nutzungsrecht: Copyright © Taylor & Francis Group, LLC construct validity multitrait-multimethod models correlated trait-correlated method model method variance method effects Monte Carlo simulation Mathematical models Grimm, Kevin J oth Widaman, Keith F oth Enthalten in Structural equation modeling Philadelphia, Pa. : Psychology Press, Taylor & Francis Group, 1994 23(2016), 6, Seite 798 (DE-627)188644075 (DE-600)1285122-X (DE-576)049955675 1070-5511 nnns volume:23 year:2016 number:6 pages:798 http://dx.doi.org/10.1080/10705511.2016.1214919 Volltext http://www.tandfonline.com/doi/abs/10.1080/10705511.2016.1214919 http://search.proquest.com/docview/1829807528 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT GBV_ILN_70 GBV_ILN_4012 31.00 AVZ AR 23 2016 6 798 |
| allfields_unstemmed |
10.1080/10705511.2016.1214919 doi PQ20161201 (DE-627)OLC1986057542 (DE-599)GBVOLC1986057542 (PRQ)i1443-3497908e07841ced838373adb9cdce20af9910de3452e49e1ea1023b423256800 (KEY)0238167220160000023000600798augmentingthecorrelatedtraitcorrelatedmethodmodelf DE-627 ger DE-627 rakwb eng 300 DE-600 31.00 bkl Castro-Schilo, Laura verfasserin aut Augmenting the Correlated Trait-Correlated Method Model for Multitrait-Multimethod Data 2016 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier We introduce an approach for ensuring empirical identification of the correlated trait-correlated method (CT-CM) model under a variety of conditions. A set of models are referred to as augmented correlated trait-correlated method (ACT-CM) models because they are based on systematically augmenting the multitrait-multimethod matrix put forth by Campbell and Fiske (1959). We show results from a Monte Carlo simulation study in which data characteristics lead to an empirically underidentified standard CT-CM model, but a well-identified fully augmented correlated trait-correlated method (FACT-CM) model. This improved identification occurs even for a model in which equality constraints are imposed on loadings on each trait factor and loadings on each method factor-a specific case shown to lead to an empirically underidentified CT-CM model. Nutzungsrecht: Copyright © Taylor & Francis Group, LLC construct validity multitrait-multimethod models correlated trait-correlated method model method variance method effects Monte Carlo simulation Mathematical models Grimm, Kevin J oth Widaman, Keith F oth Enthalten in Structural equation modeling Philadelphia, Pa. : Psychology Press, Taylor & Francis Group, 1994 23(2016), 6, Seite 798 (DE-627)188644075 (DE-600)1285122-X (DE-576)049955675 1070-5511 nnns volume:23 year:2016 number:6 pages:798 http://dx.doi.org/10.1080/10705511.2016.1214919 Volltext http://www.tandfonline.com/doi/abs/10.1080/10705511.2016.1214919 http://search.proquest.com/docview/1829807528 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT GBV_ILN_70 GBV_ILN_4012 31.00 AVZ AR 23 2016 6 798 |
| allfieldsGer |
10.1080/10705511.2016.1214919 doi PQ20161201 (DE-627)OLC1986057542 (DE-599)GBVOLC1986057542 (PRQ)i1443-3497908e07841ced838373adb9cdce20af9910de3452e49e1ea1023b423256800 (KEY)0238167220160000023000600798augmentingthecorrelatedtraitcorrelatedmethodmodelf DE-627 ger DE-627 rakwb eng 300 DE-600 31.00 bkl Castro-Schilo, Laura verfasserin aut Augmenting the Correlated Trait-Correlated Method Model for Multitrait-Multimethod Data 2016 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier We introduce an approach for ensuring empirical identification of the correlated trait-correlated method (CT-CM) model under a variety of conditions. A set of models are referred to as augmented correlated trait-correlated method (ACT-CM) models because they are based on systematically augmenting the multitrait-multimethod matrix put forth by Campbell and Fiske (1959). We show results from a Monte Carlo simulation study in which data characteristics lead to an empirically underidentified standard CT-CM model, but a well-identified fully augmented correlated trait-correlated method (FACT-CM) model. This improved identification occurs even for a model in which equality constraints are imposed on loadings on each trait factor and loadings on each method factor-a specific case shown to lead to an empirically underidentified CT-CM model. Nutzungsrecht: Copyright © Taylor & Francis Group, LLC construct validity multitrait-multimethod models correlated trait-correlated method model method variance method effects Monte Carlo simulation Mathematical models Grimm, Kevin J oth Widaman, Keith F oth Enthalten in Structural equation modeling Philadelphia, Pa. : Psychology Press, Taylor & Francis Group, 1994 23(2016), 6, Seite 798 (DE-627)188644075 (DE-600)1285122-X (DE-576)049955675 1070-5511 nnns volume:23 year:2016 number:6 pages:798 http://dx.doi.org/10.1080/10705511.2016.1214919 Volltext http://www.tandfonline.com/doi/abs/10.1080/10705511.2016.1214919 http://search.proquest.com/docview/1829807528 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT GBV_ILN_70 GBV_ILN_4012 31.00 AVZ AR 23 2016 6 798 |
| allfieldsSound |
10.1080/10705511.2016.1214919 doi PQ20161201 (DE-627)OLC1986057542 (DE-599)GBVOLC1986057542 (PRQ)i1443-3497908e07841ced838373adb9cdce20af9910de3452e49e1ea1023b423256800 (KEY)0238167220160000023000600798augmentingthecorrelatedtraitcorrelatedmethodmodelf DE-627 ger DE-627 rakwb eng 300 DE-600 31.00 bkl Castro-Schilo, Laura verfasserin aut Augmenting the Correlated Trait-Correlated Method Model for Multitrait-Multimethod Data 2016 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier We introduce an approach for ensuring empirical identification of the correlated trait-correlated method (CT-CM) model under a variety of conditions. A set of models are referred to as augmented correlated trait-correlated method (ACT-CM) models because they are based on systematically augmenting the multitrait-multimethod matrix put forth by Campbell and Fiske (1959). We show results from a Monte Carlo simulation study in which data characteristics lead to an empirically underidentified standard CT-CM model, but a well-identified fully augmented correlated trait-correlated method (FACT-CM) model. This improved identification occurs even for a model in which equality constraints are imposed on loadings on each trait factor and loadings on each method factor-a specific case shown to lead to an empirically underidentified CT-CM model. Nutzungsrecht: Copyright © Taylor & Francis Group, LLC construct validity multitrait-multimethod models correlated trait-correlated method model method variance method effects Monte Carlo simulation Mathematical models Grimm, Kevin J oth Widaman, Keith F oth Enthalten in Structural equation modeling Philadelphia, Pa. : Psychology Press, Taylor & Francis Group, 1994 23(2016), 6, Seite 798 (DE-627)188644075 (DE-600)1285122-X (DE-576)049955675 1070-5511 nnns volume:23 year:2016 number:6 pages:798 http://dx.doi.org/10.1080/10705511.2016.1214919 Volltext http://www.tandfonline.com/doi/abs/10.1080/10705511.2016.1214919 http://search.proquest.com/docview/1829807528 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT GBV_ILN_70 GBV_ILN_4012 31.00 AVZ AR 23 2016 6 798 |
| language |
English |
| source |
Enthalten in Structural equation modeling 23(2016), 6, Seite 798 volume:23 year:2016 number:6 pages:798 |
| sourceStr |
Enthalten in Structural equation modeling 23(2016), 6, Seite 798 volume:23 year:2016 number:6 pages:798 |
| format_phy_str_mv |
Article |
| institution |
findex.gbv.de |
| topic_facet |
construct validity multitrait-multimethod models correlated trait-correlated method model method variance method effects Monte Carlo simulation Mathematical models |
| dewey-raw |
300 |
| isfreeaccess_bool |
false |
| container_title |
Structural equation modeling |
| authorswithroles_txt_mv |
Castro-Schilo, Laura @@aut@@ Grimm, Kevin J @@oth@@ Widaman, Keith F @@oth@@ |
| publishDateDaySort_date |
2016-01-01T00:00:00Z |
| hierarchy_top_id |
188644075 |
| dewey-sort |
3300 |
| id |
OLC1986057542 |
| language_de |
englisch |
| fullrecord |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a2200265 4500</leader><controlfield tag="001">OLC1986057542</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20220215121158.0</controlfield><controlfield tag="007">tu</controlfield><controlfield tag="008">161202s2016 xx ||||| 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1080/10705511.2016.1214919</subfield><subfield code="2">doi</subfield></datafield><datafield tag="028" ind1="5" ind2="2"><subfield code="a">PQ20161201</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)OLC1986057542</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)GBVOLC1986057542</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(PRQ)i1443-3497908e07841ced838373adb9cdce20af9910de3452e49e1ea1023b423256800</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(KEY)0238167220160000023000600798augmentingthecorrelatedtraitcorrelatedmethodmodelf</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></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">300</subfield><subfield code="q">DE-600</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">31.00</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Castro-Schilo, Laura</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Augmenting the Correlated Trait-Correlated Method Model for Multitrait-Multimethod Data</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2016</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">ohne Hilfsmittel zu benutzen</subfield><subfield code="b">n</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Band</subfield><subfield code="b">nc</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">We introduce an approach for ensuring empirical identification of the correlated trait-correlated method (CT-CM) model under a variety of conditions. A set of models are referred to as augmented correlated trait-correlated method (ACT-CM) models because they are based on systematically augmenting the multitrait-multimethod matrix put forth by Campbell and Fiske (1959). We show results from a Monte Carlo simulation study in which data characteristics lead to an empirically underidentified standard CT-CM model, but a well-identified fully augmented correlated trait-correlated method (FACT-CM) model. This improved identification occurs even for a model in which equality constraints are imposed on loadings on each trait factor and loadings on each method factor-a specific case shown to lead to an empirically underidentified CT-CM model.</subfield></datafield><datafield tag="540" ind1=" " ind2=" "><subfield code="a">Nutzungsrecht: Copyright © Taylor & Francis Group, LLC</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">construct validity</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">multitrait-multimethod models</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">correlated trait-correlated method model</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">method variance</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">method effects</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Monte Carlo simulation</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Mathematical models</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Grimm, Kevin J</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Widaman, Keith F</subfield><subfield code="4">oth</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Structural equation modeling</subfield><subfield code="d">Philadelphia, Pa. : Psychology Press, Taylor & Francis Group, 1994</subfield><subfield code="g">23(2016), 6, Seite 798</subfield><subfield code="w">(DE-627)188644075</subfield><subfield code="w">(DE-600)1285122-X</subfield><subfield code="w">(DE-576)049955675</subfield><subfield code="x">1070-5511</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:23</subfield><subfield code="g">year:2016</subfield><subfield code="g">number:6</subfield><subfield code="g">pages:798</subfield></datafield><datafield tag="856" ind1="4" ind2="1"><subfield code="u">http://dx.doi.org/10.1080/10705511.2016.1214919</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="u">http://www.tandfonline.com/doi/abs/10.1080/10705511.2016.1214919</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="u">http://search.proquest.com/docview/1829807528</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_OLC</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-MAT</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_70</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4012</subfield></datafield><datafield tag="936" ind1="b" ind2="k"><subfield code="a">31.00</subfield><subfield code="q">AVZ</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">23</subfield><subfield code="j">2016</subfield><subfield code="e">6</subfield><subfield code="h">798</subfield></datafield></record></collection>
|
| author |
Castro-Schilo, Laura |
| spellingShingle |
Castro-Schilo, Laura ddc 300 bkl 31.00 misc construct validity misc multitrait-multimethod models misc correlated trait-correlated method model misc method variance misc method effects misc Monte Carlo simulation misc Mathematical models Augmenting the Correlated Trait-Correlated Method Model for Multitrait-Multimethod Data |
| authorStr |
Castro-Schilo, Laura |
| ppnlink_with_tag_str_mv |
@@773@@(DE-627)188644075 |
| format |
Article |
| dewey-ones |
300 - Social sciences |
| delete_txt_mv |
keep |
| author_role |
aut |
| collection |
OLC |
| remote_str |
false |
| illustrated |
Not Illustrated |
| issn |
1070-5511 |
| topic_title |
300 DE-600 31.00 bkl Augmenting the Correlated Trait-Correlated Method Model for Multitrait-Multimethod Data construct validity multitrait-multimethod models correlated trait-correlated method model method variance method effects Monte Carlo simulation Mathematical models |
| topic |
ddc 300 bkl 31.00 misc construct validity misc multitrait-multimethod models misc correlated trait-correlated method model misc method variance misc method effects misc Monte Carlo simulation misc Mathematical models |
| topic_unstemmed |
ddc 300 bkl 31.00 misc construct validity misc multitrait-multimethod models misc correlated trait-correlated method model misc method variance misc method effects misc Monte Carlo simulation misc Mathematical models |
| topic_browse |
ddc 300 bkl 31.00 misc construct validity misc multitrait-multimethod models misc correlated trait-correlated method model misc method variance misc method effects misc Monte Carlo simulation misc Mathematical models |
| format_facet |
Aufsätze Gedruckte Aufsätze |
| format_main_str_mv |
Text Zeitschrift/Artikel |
| carriertype_str_mv |
nc |
| author2_variant |
k j g kj kjg k f w kf kfw |
| hierarchy_parent_title |
Structural equation modeling |
| hierarchy_parent_id |
188644075 |
| dewey-tens |
300 - Social sciences, sociology & anthropology |
| hierarchy_top_title |
Structural equation modeling |
| isfreeaccess_txt |
false |
| familylinks_str_mv |
(DE-627)188644075 (DE-600)1285122-X (DE-576)049955675 |
| title |
Augmenting the Correlated Trait-Correlated Method Model for Multitrait-Multimethod Data |
| ctrlnum |
(DE-627)OLC1986057542 (DE-599)GBVOLC1986057542 (PRQ)i1443-3497908e07841ced838373adb9cdce20af9910de3452e49e1ea1023b423256800 (KEY)0238167220160000023000600798augmentingthecorrelatedtraitcorrelatedmethodmodelf |
| title_full |
Augmenting the Correlated Trait-Correlated Method Model for Multitrait-Multimethod Data |
| author_sort |
Castro-Schilo, Laura |
| journal |
Structural equation modeling |
| journalStr |
Structural equation modeling |
| lang_code |
eng |
| isOA_bool |
false |
| dewey-hundreds |
300 - Social sciences |
| recordtype |
marc |
| publishDateSort |
2016 |
| contenttype_str_mv |
txt |
| container_start_page |
798 |
| author_browse |
Castro-Schilo, Laura |
| container_volume |
23 |
| class |
300 DE-600 31.00 bkl |
| format_se |
Aufsätze |
| author-letter |
Castro-Schilo, Laura |
| doi_str_mv |
10.1080/10705511.2016.1214919 |
| dewey-full |
300 |
| title_sort |
augmenting the correlated trait-correlated method model for multitrait-multimethod data |
| title_auth |
Augmenting the Correlated Trait-Correlated Method Model for Multitrait-Multimethod Data |
| abstract |
We introduce an approach for ensuring empirical identification of the correlated trait-correlated method (CT-CM) model under a variety of conditions. A set of models are referred to as augmented correlated trait-correlated method (ACT-CM) models because they are based on systematically augmenting the multitrait-multimethod matrix put forth by Campbell and Fiske (1959). We show results from a Monte Carlo simulation study in which data characteristics lead to an empirically underidentified standard CT-CM model, but a well-identified fully augmented correlated trait-correlated method (FACT-CM) model. This improved identification occurs even for a model in which equality constraints are imposed on loadings on each trait factor and loadings on each method factor-a specific case shown to lead to an empirically underidentified CT-CM model. |
| abstractGer |
We introduce an approach for ensuring empirical identification of the correlated trait-correlated method (CT-CM) model under a variety of conditions. A set of models are referred to as augmented correlated trait-correlated method (ACT-CM) models because they are based on systematically augmenting the multitrait-multimethod matrix put forth by Campbell and Fiske (1959). We show results from a Monte Carlo simulation study in which data characteristics lead to an empirically underidentified standard CT-CM model, but a well-identified fully augmented correlated trait-correlated method (FACT-CM) model. This improved identification occurs even for a model in which equality constraints are imposed on loadings on each trait factor and loadings on each method factor-a specific case shown to lead to an empirically underidentified CT-CM model. |
| abstract_unstemmed |
We introduce an approach for ensuring empirical identification of the correlated trait-correlated method (CT-CM) model under a variety of conditions. A set of models are referred to as augmented correlated trait-correlated method (ACT-CM) models because they are based on systematically augmenting the multitrait-multimethod matrix put forth by Campbell and Fiske (1959). We show results from a Monte Carlo simulation study in which data characteristics lead to an empirically underidentified standard CT-CM model, but a well-identified fully augmented correlated trait-correlated method (FACT-CM) model. This improved identification occurs even for a model in which equality constraints are imposed on loadings on each trait factor and loadings on each method factor-a specific case shown to lead to an empirically underidentified CT-CM model. |
| collection_details |
GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT GBV_ILN_70 GBV_ILN_4012 |
| container_issue |
6 |
| title_short |
Augmenting the Correlated Trait-Correlated Method Model for Multitrait-Multimethod Data |
| url |
http://dx.doi.org/10.1080/10705511.2016.1214919 http://www.tandfonline.com/doi/abs/10.1080/10705511.2016.1214919 http://search.proquest.com/docview/1829807528 |
| remote_bool |
false |
| author2 |
Grimm, Kevin J Widaman, Keith F |
| author2Str |
Grimm, Kevin J Widaman, Keith F |
| ppnlink |
188644075 |
| mediatype_str_mv |
n |
| isOA_txt |
false |
| hochschulschrift_bool |
false |
| author2_role |
oth oth |
| doi_str |
10.1080/10705511.2016.1214919 |
| up_date |
2024-07-04T04:00:15.377Z |
| _version_ |
1803619522715844608 |
| fullrecord_marcxml |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a2200265 4500</leader><controlfield tag="001">OLC1986057542</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20220215121158.0</controlfield><controlfield tag="007">tu</controlfield><controlfield tag="008">161202s2016 xx ||||| 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1080/10705511.2016.1214919</subfield><subfield code="2">doi</subfield></datafield><datafield tag="028" ind1="5" ind2="2"><subfield code="a">PQ20161201</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)OLC1986057542</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)GBVOLC1986057542</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(PRQ)i1443-3497908e07841ced838373adb9cdce20af9910de3452e49e1ea1023b423256800</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(KEY)0238167220160000023000600798augmentingthecorrelatedtraitcorrelatedmethodmodelf</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></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">300</subfield><subfield code="q">DE-600</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">31.00</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Castro-Schilo, Laura</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Augmenting the Correlated Trait-Correlated Method Model for Multitrait-Multimethod Data</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2016</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">ohne Hilfsmittel zu benutzen</subfield><subfield code="b">n</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Band</subfield><subfield code="b">nc</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">We introduce an approach for ensuring empirical identification of the correlated trait-correlated method (CT-CM) model under a variety of conditions. A set of models are referred to as augmented correlated trait-correlated method (ACT-CM) models because they are based on systematically augmenting the multitrait-multimethod matrix put forth by Campbell and Fiske (1959). We show results from a Monte Carlo simulation study in which data characteristics lead to an empirically underidentified standard CT-CM model, but a well-identified fully augmented correlated trait-correlated method (FACT-CM) model. This improved identification occurs even for a model in which equality constraints are imposed on loadings on each trait factor and loadings on each method factor-a specific case shown to lead to an empirically underidentified CT-CM model.</subfield></datafield><datafield tag="540" ind1=" " ind2=" "><subfield code="a">Nutzungsrecht: Copyright © Taylor & Francis Group, LLC</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">construct validity</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">multitrait-multimethod models</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">correlated trait-correlated method model</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">method variance</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">method effects</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Monte Carlo simulation</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Mathematical models</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Grimm, Kevin J</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Widaman, Keith F</subfield><subfield code="4">oth</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Structural equation modeling</subfield><subfield code="d">Philadelphia, Pa. : Psychology Press, Taylor & Francis Group, 1994</subfield><subfield code="g">23(2016), 6, Seite 798</subfield><subfield code="w">(DE-627)188644075</subfield><subfield code="w">(DE-600)1285122-X</subfield><subfield code="w">(DE-576)049955675</subfield><subfield code="x">1070-5511</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:23</subfield><subfield code="g">year:2016</subfield><subfield code="g">number:6</subfield><subfield code="g">pages:798</subfield></datafield><datafield tag="856" ind1="4" ind2="1"><subfield code="u">http://dx.doi.org/10.1080/10705511.2016.1214919</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="u">http://www.tandfonline.com/doi/abs/10.1080/10705511.2016.1214919</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="u">http://search.proquest.com/docview/1829807528</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_OLC</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-MAT</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_70</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4012</subfield></datafield><datafield tag="936" ind1="b" ind2="k"><subfield code="a">31.00</subfield><subfield code="q">AVZ</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">23</subfield><subfield code="j">2016</subfield><subfield code="e">6</subfield><subfield code="h">798</subfield></datafield></record></collection>
|
| score |
7.4004946 |