Item Analysis of Single-Peaked Response Data

The thesis explains the fundamental difference between unipolar and bipolar measurement scales for psychological characteristics. We explore the use of correspondence analysis (CA), a technique that is similar to principal component analysis and is available in SAS and SPSS, to select items that together form a bipolar scale. CA estimates both item locations and subject locations and is a useful tool in the psychometric evaluation of bipolar measurement scales. Additionally we present a new methodology (OCM) to estimate item response functions of single-peaked items with a model-free approach.