Abstract:

The change point analysis (CPA), as one of the most widely used methods for statistical process control, is introduced to psychological and educational measurement for detection of aberrant response patterns in recent years. CPA outperforms the traditional method as follows: In addition to detecting aberrant response patterns, it can also pinpoint the locations of change points, contributing to efficient cleansing of response data. The method is employed to determine whether there is a point so that the complete sequence can be divided into two parts with different statistical properties, where person-fit statistics (PFS) is needed for quantifying the difference between two sub-sequences. Future researchers should pay more attention to multiple change points detection, making full use of other effective information like response time data, developing non-parametric indices as well as reforming the exiting person-fit statistics for polytomous and multidimensional tests, so as to enhance its applicability and power.

Key words: aberrant responses, change point analysis, cumulative summation, person-fit statistics