The split-ballot multitrait-multimethod approach: implementation and problems

Saris, Satorra, and Coenders (2004) proposed a new approach to estimate the quality of survey questions, combining the advantages of 2 existing approaches: the multitrait–multimethod (MTMM) and the split-ballot (SB) ones. Implemented in practice, this new approach led to frequent problems of nonconv...

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Detalles Bibliográficos
Autores: Revilla, Melanie, Saris, Willem E.
Tipo de recurso: artículo
Estado:Versión aceptada para publicación
Fecha de publicación:2013
País:España
Institución:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
Repositorio:Recercat. Dipósit de la Recerca de Catalunya
OAI Identifier:oai:recercat.cat:10230/46006
Acceso en línea:http://hdl.handle.net/10230/46006
http://dx.doi.org/10.1080/10705511.2013.742379
Access Level:acceso abierto
Palabra clave:Convergence
Heywood cases
Monte Carlo cimulations
Quality of survey questions
Split-ballot multitrait–multimethod approach
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spelling The split-ballot multitrait-multimethod approach: implementation and problemsRevilla, MelanieSaris, Willem E.ConvergenceHeywood casesMonte Carlo cimulationsQuality of survey questionsSplit-ballot multitrait–multimethod approachSaris, Satorra, and Coenders (2004) proposed a new approach to estimate the quality of survey questions, combining the advantages of 2 existing approaches: the multitrait–multimethod (MTMM) and the split-ballot (SB) ones. Implemented in practice, this new approach led to frequent problems of nonconvergence and improper solutions. This article uses Monte Carlo simulations to understand why the SB-MTMM is working well in some cases but not in others. The number of SB groups is a crucial element: The 3-group design is performing better. However, the 2-group design can also perform well: The analyses suggest that the interaction between the absolute values of the correlations between the traits and the relative values of the different correlations between traits plays an important role.Taylor & Francis202020202013info:eu-repo/semantics/articleinfo:eu-repo/semantics/acceptedVersionapplication/pdfapplication/pdfhttp://hdl.handle.net/10230/46006http://dx.doi.org/10.1080/10705511.2013.742379reponame:Recercat. Dipósit de la Recerca de Catalunyainstname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)InglésStructural Equation Modeling: A Multidisciplinary Journal. 2013 Jan 19;20(1):27-46© This is an Accepted Manuscript of an article published by Taylor & Francis iStructural Equation Modeling: A Multidisciplinary Journal on 2013 Jan 19, available online: http://www.tandfonline.com/10.1080/10705511.2013.742379info:eu-repo/semantics/openAccessoai:recercat.cat:10230/460062026-05-29T05:05:01Z
dc.title.none.fl_str_mv The split-ballot multitrait-multimethod approach: implementation and problems
title The split-ballot multitrait-multimethod approach: implementation and problems
spellingShingle The split-ballot multitrait-multimethod approach: implementation and problems
Revilla, Melanie
Convergence
Heywood cases
Monte Carlo cimulations
Quality of survey questions
Split-ballot multitrait–multimethod approach
title_short The split-ballot multitrait-multimethod approach: implementation and problems
title_full The split-ballot multitrait-multimethod approach: implementation and problems
title_fullStr The split-ballot multitrait-multimethod approach: implementation and problems
title_full_unstemmed The split-ballot multitrait-multimethod approach: implementation and problems
title_sort The split-ballot multitrait-multimethod approach: implementation and problems
dc.creator.none.fl_str_mv Revilla, Melanie
Saris, Willem E.
author Revilla, Melanie
author_facet Revilla, Melanie
Saris, Willem E.
author_role author
author2 Saris, Willem E.
author2_role author
dc.subject.none.fl_str_mv Convergence
Heywood cases
Monte Carlo cimulations
Quality of survey questions
Split-ballot multitrait–multimethod approach
topic Convergence
Heywood cases
Monte Carlo cimulations
Quality of survey questions
Split-ballot multitrait–multimethod approach
description Saris, Satorra, and Coenders (2004) proposed a new approach to estimate the quality of survey questions, combining the advantages of 2 existing approaches: the multitrait–multimethod (MTMM) and the split-ballot (SB) ones. Implemented in practice, this new approach led to frequent problems of nonconvergence and improper solutions. This article uses Monte Carlo simulations to understand why the SB-MTMM is working well in some cases but not in others. The number of SB groups is a crucial element: The 3-group design is performing better. However, the 2-group design can also perform well: The analyses suggest that the interaction between the absolute values of the correlations between the traits and the relative values of the different correlations between traits plays an important role.
publishDate 2013
dc.date.none.fl_str_mv 2013
2020
2020
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/acceptedVersion
format article
status_str acceptedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10230/46006
http://dx.doi.org/10.1080/10705511.2013.742379
url http://hdl.handle.net/10230/46006
http://dx.doi.org/10.1080/10705511.2013.742379
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Structural Equation Modeling: A Multidisciplinary Journal. 2013 Jan 19;20(1):27-46
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Taylor & Francis
publisher.none.fl_str_mv Taylor & Francis
dc.source.none.fl_str_mv reponame:Recercat. Dipósit de la Recerca de Catalunya
instname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
instname_str Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
reponame_str Recercat. Dipósit de la Recerca de Catalunya
collection Recercat. Dipósit de la Recerca de Catalunya
repository.name.fl_str_mv
repository.mail.fl_str_mv
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