Estimation of item location effects by means of the generalized logistic regression model: a simulation study and an application
Rainer W. Alexandrowicz, Herbert Matschinger · Psychology science · 2008
The present paper deals with the application of the generalized logistic regression model to the estimation of item location effects. A Monte Carlo study demonstrates that item difficulties and item location effects show excellent parameter recovery when distributional assumptions of the marginal maximum likelihood method are not met. A practical application to a reasoning test revealed the existence of item location effects and an effect of total test taking time. This model allows for the flexible utilization to a wide range of problems and thus provides a powerful tool for item analysis.