2015
DOI: 10.2139/ssrn.2613421
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Evaluating and Improving Item Response Theory Models for Cross-National Expert Surveys

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Cited by 56 publications
(46 citation statements)
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References 25 publications
(25 reference statements)
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“…Extensive Monte Carlo simulations provide strong evidence that bridge coders indeed improve model fit and greatly increase the degree of cross-national comparability (Pemstein et al 2015).…”
Section: Creating the V-dem Core Civil Society Indexmentioning
confidence: 94%
See 1 more Smart Citation
“…Extensive Monte Carlo simulations provide strong evidence that bridge coders indeed improve model fit and greatly increase the degree of cross-national comparability (Pemstein et al 2015).…”
Section: Creating the V-dem Core Civil Society Indexmentioning
confidence: 94%
“…In the process over 2,500 country experts worldwide have contributed ratings to V-Dem (Coppedge et al 2015b(Coppedge et al , 2015c. The country-expert data is combined into country-year estimates using a stateof-the-art Bayesian ordinal item-response theory model developed by the project's methodologists (Pemstein et al 2015). The V-Dem civil society battery has ten questions that gauge different disaggregated aspects of civil society.…”
Section: The V-dem Core Civil Society Indexmentioning
confidence: 99%
“…To explore the temporal relationship between various aspects of democracy utilizing the proposed sequence analysis approach, we use the V-Dem dataset v4 for the purposes of IRT-model for aggregating and weighting expert ratings and for calculating confidence intervals alongside a series of validity and reliability tests, including tests of intercoder reliability (see Pemstein et al 2015 andCoppedge et al 2015c). This model takes into account the possibilities that experts may make mistakes and have different scales in mind when providing judgments.…”
Section: Datamentioning
confidence: 99%
“…Therefore we use Bayesian item response theory (IRT) modeling techniques to estimate latent country coding unit characteristics from our collection of expert ratings (see Pemstein, Tzelgov and Wang 2015). The underpinnings of these measurement models are straightforward: they use patterns of cross-rater (dis)agreement to estimate variations in reliability and systematic bias across disparate measures of the same, or similar, concepts (i.e., multiple expert ratings).…”
Section: Data and Measurementmentioning
confidence: 99%
“…These are coders who code the full time series (generally 1900-2012) for more than one country covering one or more areas ("surveys"). Essentially, this coding procedure allows us to mitigate the incomparability of coders' thresholds and the problem of cross-national estimates' calibration (Pemstein et al 2015).…”
Section: Data and Measurementmentioning
confidence: 99%