LSAC Resources

Research

Computerized Testing Reports

Computerized Testing Reports:

Alphabetical Listing of All Computerized Testing Reports

Adaptive Mastery Testing Using the Rasch Model and Bayesian Sequential Decision Theory (CT 99-02)
by Cees A. W. Glas and Hans J. Vos, University of Twente, Enschede, The Netherlands

Adaptive Testing With Equated Number-Correct Scoring (CT 99-12)
by Wim J. van der Linden, University of Twente, Enschede, The Netherlands

Alternative Approaches to Updating Item Parameter Estimates in Tests With Item Cloning (CT 03-01)
by Cees A. W. Glas, University of Twente, Enschede, The Netherlands

Anchor-Based Methods for Judgmentally Estimating Item Difficulty Parameters (CT 98-05)
by Ronald K. Hambleton, Stephen G. Sireci, H. Swaminathan, Dehui Xing, and Saba Rizavi, University of Massachusetts at Amherst

Assessing Subgroup Differences in Item Response Times (CT 97-03)
by Deborah L. Schnipke and Peter J. Pashley

Assessing the Dimensionality of Simulated LSAT Item Response Matrices with Small Sample Sizes and Short Test Lengths (CT 96-01)
by André F. De Champlain

A Bayesian Approach to Item Calibration and Evaluation of Parameter Drift (CT 00-02)
by Cees A. W. Glas, University of Twente, Enschede, The Netherlands

A Bayesian Method for the Detection of Item Preknowledge in CAT (CT 98-07)
by Lori D. McLeod, Law School Admission Council; Charles Lewis, Educational Testing Service; and David Thissen, University of North Carolina at Chapel Hill

Capitalization on Item Calibration Error in Computer Adaptive Testing (CT 98-04)
by Wim J. van der Linden and Cees A. W. Glas, University of Twente, Enschede, The Netherlands

CATSIB: A Modified SIBTEST Procedure to Detect Differential Item Functioning in Computerized Adaptive Tests (CT 97-11)
by Ratna Nandakumar, University of Delaware; and Louis Roussos, Law School Admission Council

A Comparison of Item-Selection Methods for Adaptive Tests With Content Constraints (CT 04-02)
by Wim J. van der Linden, University of Twente, Enschede, The Netherlands

A Comparison Testlet-Based Test Designs for Computerized Adaptive Testing (CT 97-01)
by Deborah L. Schnipke and Lynda M. Reese

Computer Usage and Access Patterns of Actual and Potential LSAT Takers (CT 97-10)
by Susan M. Jenkins, Law School Admission Council; and Samantha D. Holmes, University of Michigan

Computer Use and Preferences Among LSAT Takers (CT 05-01)
by Ann Gallagher, Andrea E. Thornton, Deborah A. Suto, and Christopher W. T. Chiu

Computerized Adaptive Testing Simulations Using Real Test Taker Responses (CT 96-06)
by Xiang Bo Wang, WeiQin Pan, and Vincent Harris

Computerized Adaptive Testing with Item Cloning (CT 01-03)
by Cees A. W. Glas and Wim J. van der Linden, University of Twente, Enschede, The Netherlands

Computerized Adaptive Testing with Multiple Form Structures (CT 99-14)
by Ronald D. Armstrong and Douglas H. Jones, Faculty of Management, Rutgers University; Nicole B. Koppel, School of Business, Montclair State University; and Peter J. Pashley, Testing and Research, Law School Admission Council

Constraining Item Exposure in Computerized Adaptive Testing with Shadow Tests (CT 02-03)
by Wim J. van der Linden and Bernard P. Veldkamp, University of Twente, Enschede, The Netherlands

Cross Validating Item Parameter Estimation in Adaptive Testing (CT 00-04)
by Wim J. van der Linden and Cees A. Glas, University of Twente, Enschede, The Netherlands

CUSUM Statistics for Large Item Banks: Computation of Standard Errors (CT 98-11)
by C.A.W. Glas, University of Twente

Detecting Items That Have Been Memorized (CT 99-05)
by Lori McLeod and Deborah L. Schnipke

Detection of Advance Item Knowledge Using Response Times in Computer Adaptive Testing (CT 03-03)
by Rob R. Meijer and Leonardo S. Sotaridona, University of Twente, Enschede, The Netherlands

Detection of Person Misfit in Computerized Adaptive Testing with Polytomous Items (CT 00-03)
by Rob R. Meijer and Edith M. L. A. van Krimpen-Stoop, University of Twente, Enschede, The Netherlands

Development and Testing of an Innovative Listening Comprehension (LC) Item Type Interface (CT 01-05)
by Kimberly Swygert and Michael Contreras

Effects of Multidimensionality on IRT Item Characteristics and True Score Estimates: Implications for Computerized Test Assembly (CT 97-06)
by Xiang-Bo Wang, Vincent Harris, and Louis Roussos

An Empirical Bayes Enhancement of Mantel-Haenszel DIF Analysis for Computer-Adaptive Tests (CT 98-15)
by Rebecca Zwick, University of California, Santa Barbara; and Dorothy T. Thayer, Educational Testing Service

Equating an Adaptive Test to a Linear Test (CT 04-01)
by Wim J. van der Linden, University of Twente, Enschede, The Netherlands

Estimation of Item Dimensional Measurement Direction Using Conditional Covariance Patterns (CT 98-02)
by Daniel Bolt, University of Illinois at Urbana-Champaign; Louis Roussos, Law School Admission Council; and William Stout, University of Illinois at Urbana-Champaign

Evaluating Equating Error in Observed-Score Equating (CT 04-03)
by Wim J. van der Linden, University of Twente, Enschede, The Netherlands

An Evaluation of a Two-Stage Testlet Design For Computerized Testing (CT 96-04)
by Lynda M. Reese and Deborah L. Schnipke

An Evaluation of the Impact of Cloning on Item Parameters (CT 99-08)
by Kimberly A. Swygert, David J. Scrams, Louis E. Thompson, and Deborah E. Kerman

An Expected Response Function Approach to Graphical Differential Item Functioning (CT 99-01)
by David J. Scrams and Lori D. McLeod

Exploring Issues of Test Taker Behavior: Insights Gained from Response-Time Analyses (CT 98-09)
by Deborah L. Schnikpe and David J. Scrams

Exploring New Methods to Detect Person Misfit in CAT (CT 99-13)
by Rob R. Meijer and Edith M. L. A. van Krimpen-Stoop, University of Twente, Enschede, The Netherlands

Final Report: LSAC Skills Analysis Law School Task Survey (CT 02-02)
by Stephen W. Luebke, Kimberly A. Swygert, Lori D. McLeod, Susan P. Dalessandro, and Louis A. Roussos

Fixed-Weight Methods of Scoring Computer-Based Adaptive Tests (CT 97-12)
by Bert F. Green, Johns Hopkins Unversity

A Formal Characterization of and Some Alternatives to Sympson-Hetter Item-Exposure Control in Computerized Adaptive Testing (CT 02-05)
by Wim J. van der Linden, University of Twente, Enschede, The Netherlands

Formal Usability Testing of the Computerized LSAT Prototypes at the 1999 Law School Recruitment Forums (CT 01-01)
by Kimberly A. Swygert, Jennifer A. Lawlor, and Kira Shteinberg

The Impact of Item Location Effects on Ability Estimation in CAT: A Simulation Study (CT 01-06)
by Mei Liu, Law School Admission Council; and Renbang Zhu and Fanmin Guo, Educational Testing Service

The Impact of Item Parameter Estimation on Computerized Adaptive Testing with Item Cloning (CT 02-06)
by Cees A. W. Glas, University of Twente, Enschede, The Netherlands

Impact of Local Item Dependence on Item Response Theory Scoring in CAT (CT 98-08)
by Lynda M. Reese

Implementing Content Constraints in Alpha-Stratified Adaptive Testing Using a Shadow Test Approach (CT 01-09)
by Wim J. van der Linden, University of Twente, Enschede, The Netherlands; and Hua-Hua Chang, National Board of Medical Examiners

Incorporating Content Constraints into a Multi-Stage Adaptive Testlet Design (CT 97-02)
by Lynda M. Reese, Deborah L. Schnipke, and Stephen W. Luebke

The Influence of Speededness on Item-Parameter Estimation (CT 96-07)
by Deborah L. Schnipke

An Integer-programming Approach to Item Pool Design (CT 98-14)
by Wim J. van der Linden and Bernard P. Veldkamp, University of Twente; and Lynda M. Reese, Law School Admission Council

Investigating the Quality of Items in CAT Using Nonparametric IRT (CT 04-05)
by Rob R. Meijer, University of Twente, Enschede, The Netherlands

Item Parameter Calibration of LSAT Items Using MCMC Approximation of Bayes Posterior Distributions (CT 00-05)
by Douglas H. Jones and Mikhail Nediak, Rutgers, The State University of New Jersey, Department of Management Science and Information Systems

Item Theft in a Continuous-Testing Environment: What is the Extent of the Danger? (CT 98-01)
by Deborah L. Schnipke, Law School Admission Council; and David J. Scrams, Educational Testing Service

Kernel-Smoothed DIF Detection Procedure for Computerized Adaptive Tests (CT 00-08)
by Ratna Nandakumar and Julie Cwikla Banks, University of Delaware; and Louis Roussos, Law School Admission Council

Making Use of Response Times in Standardized Tests: Are Accuracy and Speed Measuring the Same Thing? (CT 97-04)
by David J. Scrams, Johns Hopkins University; and Deborah L. Schnipke, Law School Admission Council

A Method for Determining the Maximum Number of Nonoverlapping Linear Test Forms That Can Be Assembled From an Item Pool (CT 03-04)
by Ronald Armstrong, Rutgers Business School, Newark/New Brunswick, Rutgers University; and Dmitry Belov, Law School Admission Council

A Method to Determine Targets for Multi-Stage Adaptive Tests (CT 02-07)
by Ronald Armstrong, Rutgers University; and Louis Roussos, University of Illinois at Urbana-Champaign

A Model for Optimal Constrained Adaptive Testing (CT 97-07)
by Wim J. van der Linden, University of Twente; and Lynda M. Reese, Law School Admission Council

Modeling Item Response Times With a Two-State Mixture Model: A New Approach to Measuring Speededness (CT 96-02)
by Deborah L. Schnipke and David J. Scrams

Modeling Nonignorable Missing Data Processes in Item Calibration (CT 04-07)
by Cees A. W. Glas and Jonald L. Pimentel, University of Twente, Enschede, The Netherlands

Modeling Variability in Item Parameters in Educational Measurement (CT 01-07)
by Cees A. W. Glas and Wim J. van der Linden, University of Twente, Enschede, The Netherlands

Modifying Existing Dimensionality Assessment Tools for Use in a CAT Environment (CT 99-10)
by Amy Goodwin Froelich, William Stout, and Terry Ackerman, University of Illinois at Urbana-Champaign

Normal Models for Response Times on Test Items (CT 04-08)
by Wim J. van der Linden, University of Twente, Enschede, The Netherlands

On Giving Test Takers a Choice Among Constructive Response Items (CT 96-03)
by Xiang Bo Wang

On the Use of Collateral Item Response Information to Improve Pretest Item Calibration (CT 98-13)
by William Stout, Terry Ackerman, Dan Bolt, Amy Goodwin Froelich, and Dan Heck, University of Illinois at Urbana-Champaign

Optimal Assembly of Tests with Item Sets (CT 99-04)
by Wim J. van der Linden, University of Twente, Enschede, The Netherlands

Outlier Detection in High-Stakes College Entrance Testing (CT 01-08)
by Rob R. Meijer, University of Twente, Enschede, The Netherlands

A Polynomial Logistic Regression Approach to Graphical Differential Item Functioning (CT 99-06)
by Lori D. McLeod, David J. Scrams, and Louis A. Roussos

Predictability of Cloned Item Parameters (CT 99-09)
by Kimberly A. Swygert, David J. Scrams, Deborah E. Kerman, and Louis E. Thompson

Quality Control of Online Calibration in Computerized Assessment (CT 97-15)
by C. A. W. Glas, Department of Educational Measurement and Data Analysis, Faculty of Educational Science and Technology, University of Twente, Enschede, The Netherlands

The Relationship of Item-level Response Times With Test-Taker and Item Variables in an Operational CAT Environment (CT 98-10)
by Kimberly A. Swygert

Representing Response-Time Information in Item Banks (CT 97-09)
by Deborah L. Schnipke and David J. Scrams

A Review of the LSAT Using Literature on Legal Reasoning (CT 97-08)
by Gilbert E. Plumer

Robustness of Person-Fit Decisions in Computerized Adaptive Testing (CT 04-06)
by Rob R. Meijer, University of Twente, Enschede, The Netherlands

Routing Rules for Multiple-Form Structures (CT 02-08)
by Ronald D. Armstrong, Rutgers Business School, Rutgers University

Simple Nonparametric Checks for Model Data Fit in CAT (CT 01-04)
by Rob R. Meijer, University of Twente, Enschede, The Netherlands

A Simulation Study of Optimal Online Calibration of Testlets Using Real Data (CT 00-07)
by Douglas H. Jones and Mikhail S. Nediak, Rutgers, The State University of New Jersey

Simultaneous Assembly of Multiple Test Forms (CT 97-13)
by Wim J. van der Linden, University of Twente, Enschede, The Netherlands; and Jos J. Adema, PTT Telecom

Small Sample Estimation in Dichotomous Item Response Models: Effect of Priors Based on Judgmental Information on the Accuracy of Item Parameter Estimates (CT 98-06)
by Hariharan Swaninathan, Ronald K. Hambleton, Stephen G. Sireci, Dehui Xing, and Saba M. Rizavi, University of Massachusetts Amherst

Some New Methods to Detect Person Fit in CAT (CT 99-03)
by Rob Meijer and Edith M. L. A. van Krimpen-Stoop, University of Twente, Enschede, The Netherlands

Survey and Usability Testing Results of the Analytical Reasoning Computerized Prototype at the 2000 Law School Recruitment Forums (CT 02-01)
by Kimberly A. Swygert, Susan P. Dalessandro, and Mike Contreras

Survey Results From Demonstration of the Preliminary Computerized LSAT Prototypes at the 1995–1998 Law School Recruitment Forums (CT 00-01)
by Kimberly A. Swygert and Andrea E. Thornton

Survey Results From the Computerized LSAT Prototype Testing at the 1999 Law School Recruitment Forums (CT 00-06)
by Kimberly A. Swygert, Jennifer A. Lawlor, and Kira Velikopolsky

Testlet-Based Adaptive Mastery Testing (CT 99-11)
by Cees A. W. Glas and Hans J. Vos, University of Twente, Enschede, The Netherlands

Theoretical Formula for Statistical Bias in CATSIB DIF Estimates Due to Discretization of the Ability Scale (CT 99-07)
by Louis A. Roussos, Law School Admission Council; and Ratna Nandakumar and Julie Cwikla Banks, University of Delaware

Understanding Psychological Processes that Underlie Test Takers' Choices of Constructed Response Items (CT 97-05)
by Xiang Bo Wang

The Use of Person-Fit Statistics in Computerized Adaptive Testing (CT 97-14)
by Rob R. Meijer and Edith M.L.A. van Krimpen-Stoop, University of Twente, Enschede, The Netherlands

The Use of Statistical Process Control-Charts for Person-Fit Analysis in Computerized Adaptive Testing (CT 98-12)
by Rob R. Meijer and Edith M. L. A. van Krimpen-Stoop, University of Twente

Using Patterns of Summed Scores in Paper-and-Pencil Tests and CAT to Detect Misfitting Item Score Patterns (CT 02-04)
by Rob R. Meijer, University of Twente, Enschede, The Netherlands

Using Response-Time Constraints in Item Selection to Control for Differential Speededness in Computerized Adaptive Testing (CT 98-03)
by Wim J. van der Linden, University of Twente, Enschede, The Netherlands; and David J. Scrams and Deborah L. Schnipke, Virtual Psychometrics

Using Response Times to Detect Aberrant Responses in Computerized Adaptive Testing (CT 01-02)
by Wim J. van der Linden and Edith M. L. A. van Krimpen-Stoop, University of Twente, Enschede, The Netherlands

Violations of Ignorability in Computerized Adaptive Testing (CT 04-04)
by Cees A. W. Glas, University of Twente, Enschede, The Netherlands

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