A test for multigroup comparison using partial least squares path modeling

Detalhes bibliográficos
Autor(a) principal: Klesel, Michael
Data de Publicação: 2019
Outros Autores: Schuberth, Florian, Henseler, Jörg, Niehaves, Bjoern
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/91556
Resumo: Klesel, M., Schuberth, F., Henseler, J., & Niehaves, B. (2019). A test for multigroup comparison using partial least squares path modeling. Internet Research, 29(3), 464-477. https://doi.org/10.1108/IntR-11-2017-0418
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spelling A test for multigroup comparison using partial least squares path modelingMonte Carlo simulationMultigroup analysisPartial least squares path modellingPermutation testCommunicationSociology and Political ScienceEconomics and EconometricsKlesel, M., Schuberth, F., Henseler, J., & Niehaves, B. (2019). A test for multigroup comparison using partial least squares path modeling. Internet Research, 29(3), 464-477. https://doi.org/10.1108/IntR-11-2017-0418Purpose: People seem to function according to different models, which implies that in business and social sciences, heterogeneity is a rule rather than an exception. Researchers can investigate such heterogeneity through multigroup analysis (MGA). In the context of partial least squares path modeling (PLS-PM), MGA is currently applied to perform multiple comparisons of parameters across groups. However, this approach has significant drawbacks: first, the whole model is not considered when comparing groups, and second, the family-wise error rate is higher than the predefined significance level when the groups are indeed homogenous, leading to incorrect conclusions. Against this background, the purpose of this paper is to present and validate new MGA tests, which are applicable in the context of PLS-PM, and to compare their efficacy to existing approaches. Design/methodology/approach: The authors propose two tests that adopt the squared Euclidean distance and the geodesic distance to compare the model-implied indicator correlation matrix across groups. The authors employ permutation to obtain the corresponding reference distribution to draw statistical inference about group differences. A Monte Carlo simulation provides insights into the sensitivity and specificity of both permutation tests and their performance, in comparison to existing approaches. Findings: Both proposed tests provide a considerable degree of statistical power. However, the test based on the geodesic distance outperforms the test based on the squared Euclidean distance in this regard. Moreover, both proposed tests lead to rejection rates close to the predefined significance level in the case of no group differences. Hence, our proposed tests are more reliable than an uncontrolled repeated comparison approach. Research limitations/implications: Current guidelines on MGA in the context of PLS-PM should be extended by applying the proposed tests in an early phase of the analysis. Beyond our initial insights, more research is required to assess the performance of the proposed tests in different situations. Originality/value: This paper contributes to the existing PLS-PM literature by proposing two new tests to assess multigroup differences. For the first time, this allows researchers to statistically compare a whole model across groups by applying a single statistical test.NOVA Information Management School (NOVA IMS)Information Management Research Center (MagIC) - NOVA Information Management SchoolRUNKlesel, MichaelSchuberth, FlorianHenseler, JörgNiehaves, Bjoern2020-01-21T23:34:40Z2019-01-012019-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article13application/pdfhttp://hdl.handle.net/10362/91556eng1066-2243PURE: 12797924https://doi.org/10.1108/IntR-11-2017-0418info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-03-11T04:40:40Zoai:run.unl.pt:10362/91556Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:37:21.347914Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv A test for multigroup comparison using partial least squares path modeling
title A test for multigroup comparison using partial least squares path modeling
spellingShingle A test for multigroup comparison using partial least squares path modeling
Klesel, Michael
Monte Carlo simulation
Multigroup analysis
Partial least squares path modelling
Permutation test
Communication
Sociology and Political Science
Economics and Econometrics
title_short A test for multigroup comparison using partial least squares path modeling
title_full A test for multigroup comparison using partial least squares path modeling
title_fullStr A test for multigroup comparison using partial least squares path modeling
title_full_unstemmed A test for multigroup comparison using partial least squares path modeling
title_sort A test for multigroup comparison using partial least squares path modeling
author Klesel, Michael
author_facet Klesel, Michael
Schuberth, Florian
Henseler, Jörg
Niehaves, Bjoern
author_role author
author2 Schuberth, Florian
Henseler, Jörg
Niehaves, Bjoern
author2_role author
author
author
dc.contributor.none.fl_str_mv NOVA Information Management School (NOVA IMS)
Information Management Research Center (MagIC) - NOVA Information Management School
RUN
dc.contributor.author.fl_str_mv Klesel, Michael
Schuberth, Florian
Henseler, Jörg
Niehaves, Bjoern
dc.subject.por.fl_str_mv Monte Carlo simulation
Multigroup analysis
Partial least squares path modelling
Permutation test
Communication
Sociology and Political Science
Economics and Econometrics
topic Monte Carlo simulation
Multigroup analysis
Partial least squares path modelling
Permutation test
Communication
Sociology and Political Science
Economics and Econometrics
description Klesel, M., Schuberth, F., Henseler, J., & Niehaves, B. (2019). A test for multigroup comparison using partial least squares path modeling. Internet Research, 29(3), 464-477. https://doi.org/10.1108/IntR-11-2017-0418
publishDate 2019
dc.date.none.fl_str_mv 2019-01-01
2019-01-01T00:00:00Z
2020-01-21T23:34:40Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10362/91556
url http://hdl.handle.net/10362/91556
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 1066-2243
PURE: 12797924
https://doi.org/10.1108/IntR-11-2017-0418
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 13
application/pdf
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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