Academic insights: An application of multiple-group causal models in assessing cross-cultural measurement equivalence.

In cross-national marketing research, the question whether measurement accuracy, reliability, and validity are achieved across samples traditionally has hampered research efforts. Measurement equivalence across samples has particularly perplexed researchers in their efforts to evaluate responses regarding latent variables. Recently, multiple-group structural equations modeling has been suggested as a reliable method for determining measurement equivalence. To date, however, the use of this approach has remained limited. In this study, the authors apply multiple-group structural equations modeling to assess measurement equivalence in three distinct constructs across U.S. and Korean samples on data derived from cross-cultural advertising research. The authors propose an extension of this method using the measurement error covariance matrices, which will enable researchers to evaluate measurement reliability across samples better and to attempt to disentangle cultural differences in instrument usage from measurement-related differences. The authors evaluate the results and discuss the findings, as well as outline the implications and limitations of this method for further research.

Main Author: Myers, Matthew.
Other Authors: Calantone, Roger., Page, Thomas., Taylor, Charles.
Language: English
Published: 2000
Online Access: http://ezproxy.villanova.edu/login?url=https://digital.library.villanova.edu/Item/vudl:178797
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dc_source_str_mv Journal of International Marketing 8(4), 2000, 108-121.
author Myers, Matthew.
author_facet_str_mv Myers, Matthew.
Calantone, Roger.
Page, Thomas.
Taylor, Charles.
author_or_contributor_facet_str_mv Myers, Matthew.
Calantone, Roger.
Page, Thomas.
Taylor, Charles.
author_s Myers, Matthew.
spellingShingle Myers, Matthew.
Academic insights: An application of multiple-group causal models in assessing cross-cultural measurement equivalence.
author-letter Myers, Matthew.
author_sort_str Myers, Matthew.
author2 Calantone, Roger.
Page, Thomas.
Taylor, Charles.
author2Str Calantone, Roger.
Page, Thomas.
Taylor, Charles.
dc_title_str Academic insights: An application of multiple-group causal models in assessing cross-cultural measurement equivalence.
title Academic insights: An application of multiple-group causal models in assessing cross-cultural measurement equivalence.
title_short Academic insights: An application of multiple-group causal models in assessing cross-cultural measurement equivalence.
title_full Academic insights: An application of multiple-group causal models in assessing cross-cultural measurement equivalence.
title_fullStr Academic insights: An application of multiple-group causal models in assessing cross-cultural measurement equivalence.
title_full_unstemmed Academic insights: An application of multiple-group causal models in assessing cross-cultural measurement equivalence.
collection_title_sort_str academic insights: an application of multiple-group causal models in assessing cross-cultural measurement equivalence.
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description In cross-national marketing research, the question whether measurement accuracy, reliability, and validity are achieved across samples traditionally has hampered research efforts. Measurement equivalence across samples has particularly perplexed researchers in their efforts to evaluate responses regarding latent variables. Recently, multiple-group structural equations modeling has been suggested as a reliable method for determining measurement equivalence. To date, however, the use of this approach has remained limited. In this study, the authors apply multiple-group structural equations modeling to assess measurement equivalence in three distinct constructs across U.S. and Korean samples on data derived from cross-cultural advertising research. The authors propose an extension of this method using the measurement error covariance matrices, which will enable researchers to evaluate measurement reliability across samples better and to attempt to disentangle cultural differences in instrument usage from measurement-related differences. The authors evaluate the results and discuss the findings, as well as outline the implications and limitations of this method for further research.
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dc.title Academic insights: An application of multiple-group causal models in assessing cross-cultural measurement equivalence.
dc.creator Myers, Matthew.
Calantone, Roger.
Page, Thomas.
Taylor, Charles.
dc.description In cross-national marketing research, the question whether measurement accuracy, reliability, and validity are achieved across samples traditionally has hampered research efforts. Measurement equivalence across samples has particularly perplexed researchers in their efforts to evaluate responses regarding latent variables. Recently, multiple-group structural equations modeling has been suggested as a reliable method for determining measurement equivalence. To date, however, the use of this approach has remained limited. In this study, the authors apply multiple-group structural equations modeling to assess measurement equivalence in three distinct constructs across U.S. and Korean samples on data derived from cross-cultural advertising research. The authors propose an extension of this method using the measurement error covariance matrices, which will enable researchers to evaluate measurement reliability across samples better and to attempt to disentangle cultural differences in instrument usage from measurement-related differences. The authors evaluate the results and discuss the findings, as well as outline the implications and limitations of this method for further research.
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