It is common practice for assessment programs to organize qualifying sessions during which the raters (often known as "markers" or "judges") demonstrate their consistency before operational rating commences. Because of the high-stakes nature of many rating activities, the research community tends to continuously explore new…

When the parameters of item response data are estimated by a latent trait model, some variation will remain unaccounted. If baseline graphical configurations of the residual variation can be constructed, measurement irregularities may be exposed. An analytic strategy for the graphical representation and analysis of Rasch model residuals is…

This paper briefly demonstrates a few of the possibilities of a systematic application of robustness theory, concentrating on the estimation of ability when the true item response model does and does not fit the data. The definition of the maximum likelihood estimator (MLE) of ability is briefly reviewed. After introducing the notion of…

Ignorance of the characteristics of a mixed population may lead to bias in a summary measure of a phenomenon. A test based on sample kurtosis is demonstrated by a simulation study to be more powerful than six other known tests in detecting a class of mixed normal distributions. (SLD)

Data on 2,380 searches of online information retrieval systems are analyzed using a mathematical model to determine the relationship between two measures of effectiveness--documents read and relevant references. The nature and relative merits of these two variables are discussed, as well as the findings, and seven references are listed. (RBF)

The use of a three-parameter logistic model for applying latent trait theory has become more popular because of the availability of computer programs. The program Logist 5 can be used not only for the item parameter estimation in the three-parameter logistic model, but also in the two parameter logistic model by setting the third parameter equal…

Title I evaluations using the RMC Model C design depend for their interpretation on the assumption that the regression of posttest on pretest is linear across the cut score level when there is no treatment; but there are many instances where nonlinearities may occur. If one applies the analysis of covariance, or model C analysis, large errors may…