Aberrant Response Patterns on the Jordanian Version of Otis–Lennon Test and their Impact on the Accuracy of Estimating a Person's Ability and Information Function

This study aimed at investigating the aberrant response patterns and their impacts on the Jordanian version Otis- Lennon as well as the accuracy in the estimation of a person's' ability and information function test. To achieve this goal, the Jordanian version of the Ability Test primary II level form K was administrated to 568 first-grade male and female students of Ajloun district public schools during 2016/2017. The Lz person fit index and the three-parameter logistic model were used to analyze students' responses to test items to assess the person ability, information function test, and to detect aberrant response patterns. The results revealed that the response patterns of 56 students were aberrant based on Lz index; also the results showed that the factors responsible for the presence of this aberrant response were: guessing, cheating, laziness, and exponential creatively. The results indicated that when the aberrant patterns were excluded, both the accuracy person's estimating ability and the information function test had significantly increased at different ability levels.

Detecting Random Responses in a Personality Scale Using IRT-Based Person-Fit Indices

Random response is a very common aberrant response behavior in personality tests and may negatively affect the reliability, validity, or other analytical aspects of psychological assessment. Typically, researchers use a single person-fit index to identify random responses. This study recommends a three-step person-fit analysis procedure. Unlike the typical single person-fit methods, the three-step procedure identifies both global misfit and local misfit individuals using different person-fit indices. This procedure was able to identify more local misfit individuals than single-index method, and a graphical method was used to visualize those particular items in which random response behaviors appear. This method may be useful to researchers in that it will provide them with more information about response behaviors, allowing better evaluation of scale administration and development of more plausible explanations. Real data were used in this study instead of simulation data. In order to create real random responses, an experimental test administration was designed. Four different random response samples were produced using this experimental system.

Comparison Among New Residual-based Person-Fit Indices and Wright's Indices for Dichotomous Three-Parameter IRT Model with Standardized Tests

Wright's residual-based person fit indices were the first person fit indices with dichotomous IRT model and commonly used with Rasch model software. Although there were number of studies which suggested modifications to improve the statistical properties of the Wright's indices, they remained to lack good statistical properties.The study presented a new person fit index and how it can be interpreted and applied for detecting person misfit. Moreover, through a simulated data, the study investigated the statistical properties and the power rates of the new index and compared it with Wright's indices. Results showed that the new index had superior statistical properties under different test conditions and overcome the Wright's index.

Person Fit for Test Speededness

The local influence diagnostics, proposed by Cook (1986) , provide a flexible way to assess the impact of minor model perturbations on key model parameters’ estimates. In this paper, we apply the local influence idea to the detection of test speededness in a model describing nonresponse in test data, and compare this local influence approach to the optimal person fit index proposed by Drasgow and Levine (1986) , and the empirical Bayes estimate of the test speededness random effect. The performance of the methods is illustrated on the Chilean SIMCE mathematics test data. The data example indicates that the three statistics are promising when it comes to the detection of special profiles, and besides overlap to a considerable extent. Given that the statistics were developed for different purposes, they react of course differentially to the various characteristics of the response profiles, and hence also exhibit some specificity.