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        <titl xml:lang="en">Code/Syntax: Functions IPU &amp; CI.IPU - Index of Proximity to Unidimensionality (lavaan)</titl>
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        <AuthEnty affiliation="GESIS - Leibniz-Institut für Sozialwissenschaften" xml:lang="en">Bluemke, Matthias
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        </AuthEnty><AuthEnty affiliation="GESIS - Leibniz-Institut für Sozialwissenschaften" xml:lang="en">Urban, Julian
        </AuthEnty><AuthEnty affiliation="GESIS - Leibniz-Institut für Sozialwissenschaften" xml:lang="de">Urban, Julian
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        <keyword xml:lang="en">unidimensionality</keyword><keyword xml:lang="en">index of proximity to unidimensionality</keyword><keyword xml:lang="en">bifactor model</keyword><keyword xml:lang="en">psychometrics</keyword><keyword xml:lang="de">unidimensionality</keyword><keyword xml:lang="de">index of proximity to unidimensionality</keyword><keyword xml:lang="de">bifactor model</keyword><keyword xml:lang="de">psychometrics</keyword>
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      <abstract xml:lang="en">This R-code complements - and allows to reproduce and flexibly implement - Raykov &amp; Bluemke's (2021, DOI:  &lt;a href="https://doi.org/10.1177/0013164420940764" target=_blank&gt;10.1177/0013164420940764 &lt;/a&gt;) procedure for examining proximity to unidimensionality for multicomponent measuring instruments with multidimensional structure. The seminal publication provides Mplus code, whereas here we show how the method can be implemented in an open-science framework. The R-code uses latent variable modeling with the help of the lavaan-package and allows one to point and interval estimate an explained variance proportion-based index that may be considered a measure of proximity to unidimensional structure. The approach is readily utilized in educational, behavioral, and social research when it is of interest to evaluate whether a more general structure scale, test, or measuring instrument could be treated as being associated with an approximately unidimensional latent structure for some empirical purposes.  Raykov, T., &amp; Bluemke, M. (2021). Examining Multidimensional Measuring Instruments for Proximity to Unidimensional Structure Using Latent Variable Modeling. Educational and Psychological Measurement, 81(2), 319-339. https://doi.org/10.1177/0013164420940764</abstract><abstract xml:lang="de">This R-code complements - and allows to reproduce and flexibly implement - Raykov &amp; Bluemke's (2021, DOI:  &lt;a href="https://doi.org/10.1177/0013164420940764" target=_blank&gt;10.1177/0013164420940764 &lt;/a&gt;) procedure for examining proximity to unidimensionality for multicomponent measuring instruments with multidimensional structure. The seminal publication provides Mplus code, whereas here we show how the method can be implemented in an open-science framework. The R-code uses latent variable modeling with the help of the lavaan-package and allows one to point and interval estimate an explained variance proportion-based index that may be considered a measure of proximity to unidimensional structure. The approach is readily utilized in educational, behavioral, and social research when it is of interest to evaluate whether a more general structure scale, test, or measuring instrument could be treated as being associated with an approximately unidimensional latent structure for some empirical purposes.  Raykov, T., &amp; Bluemke, M. (2021). Examining Multidimensional Measuring Instruments for Proximity to Unidimensional Structure Using Latent Variable Modeling. Educational and Psychological Measurement, 81(2), 319-339. https://doi.org/10.1177/0013164420940764</abstract>
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