title: Nonparametric Estimation of Item and Respondent Locations from Unfolding-type Items.
abstract: Unlike their monotone counterparts, nonparametric unfolding response models, which assume the item response function is unimodal, have seen little attention in the psychometric literature. This paper studies the nonparametric behavior of unfolding models by building on the work of Post (1992). The paper provides rigorous justification for a class of nonparametric estimators of respondents' latent attitudes by proving that the estimators consistently rank order the respondents. The paper also suggests an algorithm for the rank ordering of items along the attitudes scale. Finally, the methods are evaluated using simulated data.
authors.affiliation: Baruch College, City University of New York, USA. Matthew_Johnson@Baruch.cuny.edu.|Department of Statistics & CIS, Baruch College, City University of New York, New York, NY, 10010, USA. Matthew_Johnson@Baruch.cuny.edu.
authors.forename: Matthew S
authors.initials: MS
authors.lastname: Johnson
keywords: Thurstone scaling; attitude scaling; ideal point models; nonparametric item response theory; unfolding response models