Modeling Measurement as a Sequential Process: Autoregressive Confirmatory Factor Analysis (AR-CFA)

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dc.citation.journalTitleFrontiers in Psychologyen_US
dc.contributor.authorOzkok, Ozlemen_US
dc.contributor.authorZyphur, Michael J.en_US
dc.contributor.authorBarsky, Adam P.en_US
dc.contributor.authorTheilacker, Maxen_US
dc.contributor.authorDonnellan, M. Brenten_US
dc.contributor.authorOswald, Frederick L.en_US
dc.date.accessioned2019-10-23T14:49:56Zen_US
dc.date.available2019-10-23T14:49:56Zen_US
dc.date.issued2019en_US
dc.description.abstractTo model data from multi-item scales, many researchers default to a confirmatory factor analysis (CFA) approach that restricts cross-loadings and residual correlations to zero. This often leads to problems of measurement-model misfit while also ignoring theoretically relevant alternatives. Existing research mostly offers solutions by relaxing assumptions about cross-loadings and allowing residual correlations. However, such approaches are critiqued as being weak on theory and/or indicative of problematic measurement scales. We offer a theoretically-grounded alternative to modeling survey data called an autoregressive confirmatory factor analysis (AR-CFA), which is motivated by recognizing that responding to survey items is a sequential process that may create temporal dependencies among scale items. We compare an AR-CFA to other common approaches using a sample of 8,569 people measured along five common personality factors, showing how the AR-CFA can improve model fit and offer evidence of increased construct validity. We then introduce methods for testing AR-CFA hypotheses, including cross-level moderation effects using latent interactions among stable factors and time-varying residuals. We recommend considering the AR-CFA as a useful complement to other existing approaches and treat AR-CFA limitations.en_US
dc.description.sponsorshipFondren Library Open Access Author Funden_US
dc.identifier.citationOzkok, Ozlem, Zyphur, Michael J., Barsky, Adam P., et al.. "Modeling Measurement as a Sequential Process: Autoregressive Confirmatory Factor Analysis (AR-CFA)." <i>Frontiers in Psychology,</i> (2019) Frontiers: https://doi.org/10.3389/fpsyg.2019.02108.en_US
dc.identifier.doihttps://doi.org/10.3389/fpsyg.2019.02108en_US
dc.identifier.urihttps://hdl.handle.net/1911/107486en_US
dc.language.isoengen_US
dc.publisherFrontiersen_US
dc.rightsThis is an open-access article distributed under the terms of theﾠCreative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.en_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_US
dc.titleModeling Measurement as a Sequential Process: Autoregressive Confirmatory Factor Analysis (AR-CFA)en_US
dc.typeJournal articleen_US
dc.type.dcmiTexten_US
dc.type.publicationpublisher versionen_US
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