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dc.contributor.authorPemstein, Daniel
dc.contributor.authorMarquardt, Kyle L.
dc.contributor.authorTzelgov, Eitan
dc.contributor.authorWang, Yi-ting
dc.contributor.authorMedzihorsky, Juraj
dc.contributor.authorKrusell, Joshua
dc.contributor.authorMiri, Farhad
dc.contributor.authorRömer, Johannes von
dc.date.accessioned2021-03-08T11:41:33Z
dc.date.available2021-03-08T11:41:33Z
dc.date.issued2022-03
dc.identifier.urihttp://hdl.handle.net/2077/67993
dc.description.abstractThe Varieties of Democracy (V–Dem) project relies on country experts who code a host of ordinal variables, providing subjective ratings of latent—that is, not directly observable—regime characteristics over time. Sets of around five experts rate each case (country-year observation), and each of these raters works independently. Since raters may diverge in their coding because of either differences of opinion or mistakes, we require systematic tools with which to model these patterns of disagreement. These tools allow us to aggregate ratings into point estimates of latent concepts and quantify our uncertainty around these point estimates. In this paper we describe item response theory models that can that account and adjust for differential item functioning (i.e. differences in how experts apply ordinal scales to cases) and variation in rater reliability (i.e. random error). We also discuss key challenges specific to applying item response theory to expert-coded cross-national panel data, explain the approaches that we use to address these challenges, highlight potential problems with our current framework, and describe long-term plans for improving our models and estimates. Finally, we provide an overview of the different forms in which we present model output.sv
dc.language.isoengsv
dc.relation.ispartofseriesWorking Paperssv
dc.relation.ispartofseries21, 7th editionsv
dc.relation.urihttps://www.v-dem.net/media/filer_public/d4/d2/d4d27532-96a7-4f8c-8028-4c356fb1b2ca/wp_21_6th_edition.pdfsv
dc.titleThe V–Dem Measurement Model: Latent Variable Analysis for Cross-National and Cross-Temporal Expert-Coded Datasv
dc.typeTextsv
dc.contributor.organizationV-Dem Institutesv


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