Questions To Ask When Evaluating Tests

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Reducing Errors Due to the Use of Judges

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Expected Classification Accuracy

Every time we make a classification based on a test score, we should expect some number of misclassifications. Some examinees whose true ability is within a score range will have observed scores outside of that range. A procedure for providing a classification table of true and expected scores is developed for polytomously scored items under item response theory and applied to state assessment data. A simplified procedure for estimating the table entries is also presented. Accessed 19,668 times on https://pareonline.net from August 29, 2005 to December 31, 2019. For downloads from January 1, 2020 forward, please click on the PlumX Metrics link to the right

Computing the expected proportions of misclassified examinees

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Item Banking

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Scoring and classifying examinees using measurement decision theory

This paper describes and evaluates the use of measurement decision theory (MDT) to classify examinees based on their item response patterns. The model has a simple framework that starts with the conditional probabilities of examinees in each category or mastery state responding correctly to each item. The presented evaluation investigates: (1) the classification accuracy of tests scored using decision theory; (2) the effectiveness of different sequential testing procedures; and (3) the number of items needed to make a classification. A large percentage of examinees can be classified accurately with very few items using decision theory. A Java Applet for self instruction and software for generating, calibrating and scoring MDT data are provided. Accessed 13,741 times on https://pareonline.net from April 11, 2009 to December 31, 2019. For downloads from January 1, 2020 forward, please click on the PlumX Metrics link to the right

Consider Propensity Scores to Compare Treatments

The underlying question when comparing treatments is usually whether an individual would do better with treatment X than they would with treatment Y. But there are often practical and theoretical problems in giving people both treatments and comparing the data. This paper presents the use of propensity score matching as a methodology that can be used to compare the effectiveness of different treatments. The method is applied to answer two questions: (1) “Should examinees take a college admissions test near or a few years after graduation?” and (2) “Do accommodated students receive an unfair advantage?” Data from a large admission testing program is used. Accessed 18,071 times on https://pareonline.net from November 17, 2006 to December 31, 2019. For downloads from January 1, 2020 forward, please click on the PlumX Metrics link to the right

Person-Fit Statistics: High Potential and Many Unanswered Questions

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An overview of three approaches to scoring written essays by computer

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Authorship Ethics

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