Item Analysis

Effects of automatic item eliminations based on item test analysis.

Item test analysis is an aid to identify items that need to be eliminated from an assessment. An automatic elimination procedure based on item statistics, therefore, could help to increase the quality of a test in an objective manner. This was investigated by studying the effect of a standardized elimination procedure on the test results of a second-year course over a period of 6 successive yea...

Part III Item - Level Analysis

Random intercept item factor analysis.

The common factor model assumes that the linear coefficients (intercepts and factor loadings) linking the observed variables to the latent factors are fixed coefficients (i.e., common for all participants). When the observed variables are participants' observed responses to stimuli, such as their responses to the items of a questionnaire, the assumption of common linear coefficients may be too ...

Generalized full-information item bifactor analysis.

Full-information item bifactor analysis is an important statistical method in psychological and educational measurement. Current methods are limited to single-group analysis and inflexible in the types of item response models supported. We propose a flexible multiple-group item bifactor analysis framework that supports a variety of multidimensional item response theory models for an arbitrary m...

An Individualistic Approach to Item Analysis

Traditionally the properties of a psychological test are defined in terms of variations within some specified population. In practice such populations may be selected in various reasonable ways, and accordingly the properties referred to—for example, the reliability coefficient —are not specific to the test itself but may vary according to how the population is defined. Similarly, the evaluatio...