KakaoBEJZ: Macro for item analysis of dichotomously scored items - item response theory
Keywords:item analysis, Item response theory, maximum likelihood estimation, Bayes theorem
AbstractThe paper presents KakaoBejz, one of the macros from the set called Kakao. This set of programs is intended for the item analysis of instruments in the field of behavioral sciences. It is developed in Matrix program language as macros for statistical package SPSS for Windows. These macros are open source programs, which are free and very simple to use. They can run only within SPSS statistical package. KakaoBejz is intended for the item analysis based on Item Response Theory (IRT). Item parameters estimation is based on the maximum likelihood method with added a priory expectations derived from the Bayes Theorem. The macro contains basic indicators of convergence control, enabling a user to assess if the iterative process is carried out correctly. By using the macro’s entry options, it is possible to control program execution, choose item response model and set starting values. KakaoBejz accepts only dichotomously scored items. Items must be scored in the same direction.
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How to Cite
Fajgelj, S., & Janičić, B. (2008). KakaoBEJZ: Macro for item analysis of dichotomously scored items - item response theory. Primenjena Psihologija, 1(3-4), 223–241. https://doi.org/10.19090/pp.2008.3-4.223-241