title: A modular approach for item response theory modeling with the R package flirt.
abstract: The new R package flirt is introduced for flexible item response theory (IRT) modeling of psychological, educational, and behavior assessment data. flirt integrates a generalized linear and nonlinear mixed modeling framework with graphical model theory. The graphical model framework allows for efficient maximum likelihood estimation. The key feature of flirt is its modular approach to facilitate convenient and flexible model specifications. Researchers can construct customized IRT models by simply selecting various modeling modules, such as parametric forms, number of dimensions, item and person covariates, person groups, link functions, etc. In this paper, we describe major features of flirt and provide examples to illustrate how flirt works in practice.
authors.affiliation: Department of Psychology, Faculty of Quantitative Psychology, The Ohio State University, 228 Lazenby Hall 1827 Neil Avenue, Columbus, OH, 43210, USA. jeon.117@osu.edu.
authors.forename: Minjeong
authors.initials: M
authors.lastname: Jeon
authors.affiliation: CTB/McGraw-Hill, New York, USA.
authors.forename: Frank
authors.initials: F
authors.lastname: Rijmen
mesh_terms: D000465:Algorithms; D001519:Behavior; D004521:Educational Measurement; D006801:Humans; D016013:Likelihood Functions; D016014:Linear Models; D008960:Models, Psychological; D017711:Nonlinear Dynamics; D011582:Psychological Theory; D012984:Software
keywords: Bifactor models; DIF; Explanatory models; Item response theory; Modular approach; Multidimensional models; R software