eng TQMP The Quantitative Methods for Psychology 1913-4126 2020-09-12 16 4 363 375 10.20982/tqmp.16.4.p363 article Rajlic, Gordana grajlic@gmail.com a University of British Columbia The current demonstration was conducted to familiarize a broader audience of applied researchers in psychology and social sciences with the benefits of an exploratory psychometric technique -- kernel smoothing item response theory (KSIRT). A data-driven, nonparametric KSIRT provides a visual representation of the characteristics of the items in a measure (scale or test) and offers convenient preliminary feedback about the functioning of the items and the measure in a particular research context. The technique could be a useful addition to the analytical toolkit of applied researchers that work with a range of measures, within the classical test theory or IRT framework. KSIRT is described and its use is demonstrated with a set of items from a psychological well-being measure. A recently developed, easy to use R package was utilized to perform the analyses and the R code is included in the manuscript. https://www.tqmp.org/RegularArticles/vol16-4/p363/p363.pdf exploratory psychometric analysis IRT kernel smoothing nonparametric regression visualization R