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There are now a number of alternative models, estimators, and software packages that researchers can use to recover latent issue or ideological spaces from voting data. These different tools usually produce substantively similar estimates, but important differences also arise. We investigated the sources of observed differences between two leading methods, NOMINATE and IDEAL. Our Monte Carlo experiments revealed that neither model has a clear advantage over the other in the recovery of legislator locations or roll-call midpoints in either large or small legislatures. These are opportunities to improve the interpretation of your content by users in different locales.

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