Kelley's Discrimination Index (DI) is a simple and robust, classical non-parametric short-cut to estimate the item discrimination power (IDP) in the practical educational settings. Unlike item-total correlation, DI can reach the ultimate values of +1 and -1, and it is stable against the outliers. Because of the computational easiness, DI is…

This study aimed to assess the accuracy of the empirical item characteristic curve (EICC) preequating method given the presence of test speededness. The simulation design of this study considered the proportion of speededness, speededness point, speededness rate, proportion of missing on speeded items, sample size, and test length. After crossing…

Measurement invariance is crucial for an effective and valid measure of a construct. Invariance holds when the latent trait varies consistently across subgroups; in other words, the mean differences among subgroups are only due to true latent ability differences. Differential item functioning (DIF) occurs when measurement invariance is violated.…

Detection of differential item functioning (DIF) by use of the logistic modeling approach has a long tradition. One big advantage of the approach is that it can be used to investigate nonuniform (NUDIF) as well as uniform DIF (UDIF). The classical approach allows one to detect DIF by distinguishing between multiple groups. We propose an…

In this report, systematic applications of statistical and psychometric methods are used to develop and evaluate scoring rules in terms of test reliability. Data collected from a situational judgment test are used to facilitate the comparison. For a well-developed item with appropriate keys (i.e., the correct answers), agreement among various…

Standard approaches for estimating item response theory (IRT) model parameters generally work under the assumption that the latent trait being measured by a set of items follows the normal distribution. Estimation of IRT parameters in the presence of nonnormal latent traits has been shown to generate biased person and item parameter estimates. A…

This paper presents a non-parametric imputation technique, named random forest, from the machine learning field. The random forest procedure has two main tuning parameters: the number of trees grown in the prediction and the number of predictors used. Fifty experimental conditions were created in the imputation procedure, with different…

The Mantel-Haenszel (MH) procedure is commonly used to detect items that function differentially for groups of examinees from various demographic and linguistic backgrounds--for example, in international assessments. As in some other DIF methods, the total score is used to match examinees on ability. In thin matching, each of the total score…

Testing strategies can either have a very positive or negative effect on the learning process. The aim of this study was to examine the degree of consistency in evaluating the practicality and logic of questions from a medical school pathophysiology test, between students and family medicine doctors. The study engaged 77 family medicine doctors…

The purpose of this study is to develop an achievement test which includes the basic concepts about the subject of sound and its properties in middle school science lessons and which at the same time aims to reveal the alternative concepts that the students already have. During the process of the development of the test, studies in the field and…

Differential item functioning (DIF) occurs when an item on a test, questionnaire, or interview has different measurement properties for one group of people versus another. One way to test items with ordinal response scales for DIF is likelihood ratio (LR) testing using item response theory (IRT), or IRT-LR-DIF. Despite the various advantages of…

A nonparametric tree classification procedure is used to detect differential item functioning for items that are dichotomously scored. Classification trees are shown to be an alternative procedure to detect differential item functioning other than the use of traditional Mantel-Haenszel and logistic regression analysis. A nonparametric…

Person-fit methods are used to uncover atypical test performance as reflected in the pattern of scores on individual items in a test. Unlike parametric person-fit statistics, nonparametric person-fit statistics do not require fitting a parametric test theory model. This study investigates the effectiveness of generalizations of nonparametric…

This study applied nonparametric bootstrapping to test null hypotheses for selected statistics (KR-20, difficulty, and discrimination) derived from a student-made test. The test, administered to 21 students enrolled in a graduate-level educational assessment class, contained 42 items, 33 of which were analyzed. Random permutations of the data…