A Latent Ability Model for Count Data and Application to Processing Speed. (November 2014)

• Record Type: Journal Article
• Authors: Doebler, Anna; Doebler, Philipp; Holling, Heinz
• Is Part Of: Applied psychological measurement. Volume 38:Number 8(2014)
• Page Start: 587
• Page End: 598
• Publication Date: 2014-11
• Subjects: count data -- Rasch Poisson counts model -- item characteristic curve -- processing speed; Psychometrics -- Periodicals; Psychological tests -- Periodicals; Psychology, Applied -- Periodicals; 150.1519505
• DOI: 10.1177/0146621614543513
• Languages: English
• ISSNs: 0146-6216

Abstract

A new family of item response theory models for count data, based on item characteristic curves (ICCs) of binary models, is presented. These models assume a Poisson distribution for the observed scores where the mean is given by the product of a speed parameter and an ICC, for example, the curve of the one- or two-parameter logistic model. Joint and marginal maximum likelihood parameter estimations are discussed and the proposed procedures are evaluated by computer simulation. As an application, item level data from a test measuring processing speed are analyzed and item fit and test information are explored.