TY - JOUR T1 - Using response times to detect aberrant responses in computerized adaptive testing JF - Psychometrika Y1 - 2003 A1 - van der Linden, W. J. A1 - van Krimpen-Stoop, E. M. L. A. KW - Adaptive Testing KW - Behavior KW - Computer Assisted Testing KW - computerized adaptive testing KW - Models KW - person Fit KW - Prediction KW - Reaction Time AB - A lognormal model for response times is used to check response times for aberrances in examinee behavior on computerized adaptive tests. Both classical procedures and Bayesian posterior predictive checks are presented. For a fixed examinee, responses and response times are independent; checks based on response times offer thus information independent of the results of checks on response patterns. Empirical examples of the use of classical and Bayesian checks for detecting two different types of aberrances in response times are presented. The detection rates for the Bayesian checks outperformed those for the classical checks, but at the cost of higher false-alarm rates. A guideline for the choice between the two types of checks is offered. VL - 68 ER - TY - JOUR T1 - An exploratory analysis of item parameters and characteristics that influence item level response time JF - Dissertation Abstracts International Section A: Humanities and Social Sciences Y1 - 2000 A1 - Smith, Russell Winsor KW - Item Analysis (Statistical) KW - Item Response Theory KW - Problem Solving KW - Reaction Time KW - Reading Comprehension KW - Reasoning AB - This research examines the relationship between item level response time and (1) item discrimination, (2) item difficulty, (3) word count, (4) item type, and (5) whether a figure is included in an item. Data are from the Graduate Management Admission Test, which is currently offered only as a computerized adaptive test. Analyses revealed significant differences in response time between the five item types: problem solving, data sufficiency, sentence correction, critical reasoning, and reading comprehension. For this reason, the planned pairwise and complex analyses were run within each item type. Pairwise curvilinear regression analyses explored the relationship between response time and item discrimination, item difficulty, and word count. Item difficulty significantly contributed to the prediction of response time for each item type; two of the relationships were significantly quadratic. Item discrimination significantly contributed to the prediction of response time for only two of the item types; one revealed a quadratic relationship and the other a cubic relationship. Word count had significant linear relationship with response time for all the item types except reading comprehension, for which there was no significant relationship. Multiple regression analyses using word count, item difficulty, and item discrimination predicted between 35.4% and 71.4% of the variability in item response time across item types. The results suggest that response time research should consider the type of item that is being administered and continue to explore curvilinear relationships between response time and its predictor variables. (PsycINFO Database Record (c) 2005 APA ) VL - 61 ER -