Measuring Non-electoral Political Participation: Bi-factor Model as a Tool to Extract Dimensions

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Abstract

Political participation is a mainstay of political behavior research. One of the main dilemmas many researchers face pertains to the number of dimensions of political participation, i.e. whether we should model political participation as a unidimensional or multidimensional latent construct. Over the years, scholars usually have favored the solution with more than one dimension of political participation and they have backed the claim of multiple dimensions with a number of empirical tests. In this paper, I argue that the results from the frequently used testing procedures which rely on the model fit inspection and the Kaiser criterion can be very misleading and may yield in extracting too many dimensions. By employing bi-factor modeling to a European Social Survey dataset, I show that in a majority of countries political participation can be considered an essentially unidimensional latent quantity. I demonstrate that additional dimensions of political participation are very weak and unreliable and that we cannot regress them on external variables nor build composite scores based on them. These findings cast doubt on the conclusions of numerous previous studies where researchers modeled more than one dimension of political participation.

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Koc, P. (2021). Measuring Non-electoral Political Participation: Bi-factor Model as a Tool to Extract Dimensions. Social Indicators Research, 156(1), 271–287. https://doi.org/10.1007/s11205-021-02637-3

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