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Below results based on the criteria 'latent variables'
Total number of records returned: 3
Democracy as a Latent Variable
latent class analysis
Markov chain Monte Carlo
Measurement is critical to the social scientific enterprise. Many key concepts in social-scientific theories are not observed directly, and researchers rely on assumptions (tacitly or explicitly, via formal measurement models) to operationalize these concepts in empirical work. In this paper we apply formal, statistical measurement models to the Polity indicators of democracy and autocracy, used widely in studies of international relations. In so doing, we make explicit the hitherto implicit assumptions underlying scales built using the Polity indicators. We discuss two models: one in which democracy is operationalized as a latent continuous variable, and another in which democracy is operationalized as a latent class. Our modeling approaches allow us to assess the measurement error in the resulting measure of democracy. We show that this measurement error is considerable, and has substantive consequences when using a measure of democracy as an independent variable in cross-national statistical analysis. Our analysis suggests that skepticism as to the precision of the Polity democracy scale is well-founded, and that many researchers have been overly sanguine about the properties of the Polity democracy scale in applied statistical work.
A Mixed-Membership Approach to the Assessment of Political Ideology from Survey Responses
latent structure model
discrete factor analysis
We employ mixed-membership (or grade-of-membership) techniques--of growing popularity in medical diagnostics, psychology, genetics, and machine learning--in order to identify prototypical profiles of survey respondents based on their answers to questions aimed at uncovering their basic orientations or ideological predispositions. In contrast with factor analytic techniques and IRT approaches, we treat both manifest and latent variables as categorical. A mixed membership model may be thought of as a generalization of latent class modeling, in which individuals act as members of more than one class. This notion is well-aligned with earlier theoretical work of Zaller, Feldman, Stimson, and others, who at times envision respondents to be internally complex, answering survey questions probabilistically according to what Zaller calls varying ``considerations.'' Reanalyzing data in this way, we develop new insights into the sorts of constraints that may structure mass belief systems.
Latent Variables and Rolling Panels: A New Approach to Modeling Campaign Effects
Election panels which reinterview participants in rolling cross-sectional surveys offer new opportunities to study campaign effects, but also present unique methodological challenges. I develop an original approach to modeling this data, and demonstrate how its application leads to much stronger evidence for informing and persuasion effects from campaign ads than that found in existing research