A test for multigroup comparison using partial least squares path modeling
Autor(a) principal: | |
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Data de Publicação: | 2019 |
Outros Autores: | , , |
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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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 |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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RCAAP |
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RCAAP |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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