Measurement Invariance
Multi-item surveys are frequently used to study scores on latent factors, like human values, attitudes and behavior. Such studies often include a comparison, between specific groups of individuals, either at one or multiple points in time. If such latent factor means are to be meaningfully compared,...
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| Natura: | Online |
| Lingua: | inglese |
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Frontiers Media SA
2021
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| Accesso online: | 19553 |
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| _version_ | 1869521845199306752 |
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| author | Peter Schmidt Alain De Beuckelaer Rens Van De Schoot |
| author_browse | Alain De Beuckelaer Peter Schmidt Rens Van De Schoot |
| author_facet | Peter Schmidt Alain De Beuckelaer Rens Van De Schoot |
| author_sort | Peter Schmidt |
| collection | Directory of Open Access Books |
| description | Multi-item surveys are frequently used to study scores on latent factors, like human values, attitudes and behavior. Such studies often include a comparison, between specific groups of individuals, either at one or multiple points in time. If such latent factor means are to be meaningfully compared, the measurement structures including the latent factor and their survey items should be stable across groups and/or over time, that is ‘invariant’. Recent developments in statistics have provided new analytical tools for assessing measurement invariance (MI). The aim of this special issue is to provide a forum for a discussion of MI, covering some crucial ‘themes’: (1) ways to assess and deal with measurement non-invariance; (2) Bayesian and IRT methods employing the concept of approximate measurement invariance; and (3) new or adjusted approaches for testing MI to fit increasingly complex statistical models and specific characteristics of survey data. The special issue started with a kick-off meeting where all potential contributors shared ideas on potential papers. This expert workshop was organized at Utrecht University in The Netherlands and was funded by the Netherlands Organization for Scientific Research (NWO-VENI-451-11-008). After the kick-off meeting the authors submitted their papers, all of which were reviewed by experts in the field. The papers in the eBook are listed in alphabetical order, but in the editorial the papers are introduced thematically. Although it is impossible to cover all areas of relevant research in the field of MI, papers in this eBook provide insight on important aspects of measurement invariance. We hope that the discussions included in this special issue will stimulate further research on MI and facilitate further discussions to support the understanding of the role of MI in multi-item surveys. |
| format | Online |
| id | doab-20.500.12854ir-52915 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2021 |
| publishDateRange | 2021 |
| publishDateSort | 2021 |
| publisher | Frontiers Media SA |
| publisherStr | Frontiers Media SA |
| record_format | ojs |
| spelling | doab-20.500.12854ir-529152024-03-29T08:00:48Z Measurement Invariance Peter Schmidt Alain De Beuckelaer Rens Van De Schoot BF1-990 Q1-390 Non-invariance Partial Invariance Structural Equation Modeling bayesian statistics cross national surveys Measurement invariance Approximate invariance multiple group analysis bic Book Industry Communication::J Society & social sciences::JM Psychology thema EDItEUR::J Society and Social Sciences::JM Psychology Multi-item surveys are frequently used to study scores on latent factors, like human values, attitudes and behavior. Such studies often include a comparison, between specific groups of individuals, either at one or multiple points in time. If such latent factor means are to be meaningfully compared, the measurement structures including the latent factor and their survey items should be stable across groups and/or over time, that is ‘invariant’. Recent developments in statistics have provided new analytical tools for assessing measurement invariance (MI). The aim of this special issue is to provide a forum for a discussion of MI, covering some crucial ‘themes’: (1) ways to assess and deal with measurement non-invariance; (2) Bayesian and IRT methods employing the concept of approximate measurement invariance; and (3) new or adjusted approaches for testing MI to fit increasingly complex statistical models and specific characteristics of survey data. The special issue started with a kick-off meeting where all potential contributors shared ideas on potential papers. This expert workshop was organized at Utrecht University in The Netherlands and was funded by the Netherlands Organization for Scientific Research (NWO-VENI-451-11-008). After the kick-off meeting the authors submitted their papers, all of which were reviewed by experts in the field. The papers in the eBook are listed in alphabetical order, but in the editorial the papers are introduced thematically. Although it is impossible to cover all areas of relevant research in the field of MI, papers in this eBook provide insight on important aspects of measurement invariance. We hope that the discussions included in this special issue will stimulate further research on MI and facilitate further discussions to support the understanding of the role of MI in multi-item surveys. 2021-02-11T18:57:53Z 2021-02-11T18:57:53Z 2016-08-16 10:34:25 2015 book 19553 16648714 9782889196500 https://directory.doabooks.org/handle/20.500.12854/52915 eng Frontiers Research Topics image/jpeg Attribution 4.0 International http://www.frontiersin.org/books/Measurement_Invariance/694#nogo http://journal.frontiersin.org/researchtopic/1695/measurement-invariance Frontiers Media SA 10.3389/978-2-88919-650-0 10.3389/978-2-88919-650-0 bf5ce210-e72e-4860-ba9b-c305640ff3ae 9782889196500 217 open access |
| spellingShingle | BF1-990 Q1-390 Non-invariance Partial Invariance Structural Equation Modeling bayesian statistics cross national surveys Measurement invariance Approximate invariance multiple group analysis bic Book Industry Communication::J Society & social sciences::JM Psychology thema EDItEUR::J Society and Social Sciences::JM Psychology Peter Schmidt Alain De Beuckelaer Rens Van De Schoot Measurement Invariance |
| title | Measurement Invariance |
| title_full | Measurement Invariance |
| title_fullStr | Measurement Invariance |
| title_full_unstemmed | Measurement Invariance |
| title_short | Measurement Invariance |
| title_sort | measurement invariance |
| topic | BF1-990 Q1-390 Non-invariance Partial Invariance Structural Equation Modeling bayesian statistics cross national surveys Measurement invariance Approximate invariance multiple group analysis bic Book Industry Communication::J Society & social sciences::JM Psychology thema EDItEUR::J Society and Social Sciences::JM Psychology |
| topic_facet | BF1-990 Q1-390 Non-invariance Partial Invariance Structural Equation Modeling bayesian statistics cross national surveys Measurement invariance Approximate invariance multiple group analysis bic Book Industry Communication::J Society & social sciences::JM Psychology thema EDItEUR::J Society and Social Sciences::JM Psychology |
| url | 19553 |
| work_keys_str_mv | AT peterschmidt measurementinvariance AT alaindebeuckelaer measurementinvariance AT rensvandeschoot measurementinvariance |