LSAC Resources - Research

Alphabetical Listing of Current Research Reports

Application of Heuristic-Based Semantic Similarity Between Single-Topic Texts for the LSAT (RR 12-05)
by Dmitry I. Belov and David A. Kary

• Application of Heuristic-Based Semantic Similarity Between Single-Topic Texts for the LSAT (RR 12-05) - Executive Summary
• Application of Heuristic-Based Semantic Similarity Between Single-Topic Texts for the LSAT (RR 12-05) - Full Research Report (PDF)

Application of the M-Index for the LSAT (RR 10-01)
by Dmitry I. Belov, Law School Admission Council; and Ronald D. Armstrong, Rutgers University

• Application of the M-Index for the LSAT (RR 10-01) - Executive Summary
• Application of the M-Index for the LSAT (RR 10-01) - Full Research Report (PDF)

Application of Robust Optimization to Automated Test Assembly (RR 12-02)
by Bernard P. Veldkamp, University of Twente, Enschede, The Netherlands

• Application of Robust Optimization to Automated Test Assembly (RR 12-02) - Executive Summary
• Application of Robust Optimization to Automated Test Assembly (RR 12-02) - Full Research Report (PDF)

An Application of the VM-Index for the LSAT (RR 10-02)
by Dmitry I. Belov

• An Application of the VM-Index for the LSAT (RR 10-02) - Executive Summary
• An Application of the VM-Index for the LSAT (RR 10-02)- Full Research Report (PDF)

Applications of Uniform Test Assembly for the LSAT (RR 05-01)
by Dmitry I. Belov

• Applications of Uniform Test Assembly for the LSAT (RR 05-01) - Executive Summary
• Applications of Uniform Test Assembly for the LSAT (RR 05-01) - Full Research Report (PDF)

Assessing the Impact of Topic Interest on Comprehension Processes (RR 11-02)
by Joseph P. Magliano, Amanda M. Durik, and Janet K. Holt, Northern Illinois University

• Assessing the Impact of Topic Interest on Comprehension Processes (RR 11-02) - Executive Summary
• Assessing the Impact of Topic Interest on Comprehension Processes (RR 11-02) - Full Research Report (PDF)

Automatic Prediction of Item Difficulty Based on Semantic Similarity Measures (RR 08-04)
by Dmitry I. Belov and Lily Knezevich

• Automatic Prediction of Item Difficulty Based on Semantic Similarity Measures (RR 08-04) - Executive Summary
• Automatic Prediction of Item Difficulty Based on Semantic Similarity Measures (RR 08-04) - Full Research Report (PDF)

Balanced Item Pool Assembly in Computerized Adaptive Testing (RR 07-04)
by Dmitry I. Belov

• Balanced Item Pool Assembly in Computerized Adaptive Testing (RR 07-04) - Executive Summary
• Balanced Item Pool Assembly in Computerized Adaptive Testing (RR 07-04) - Full Research Report (PDF)

Bayesian Estimation Methods for Multidimensional Models for Discrete and Continuous Responses (RR 06-05)
by Cees A. W. Glas, University of Twente, Enschede, The Netherlands

• Bayesian Estimation Methods for Multidimensional Models for Discrete and Continuous Responses (RR 06-05) - Executive Summary
• Bayesian Estimation Methods for Multidimensional Models for Discrete and Continuous Responses (RR 06-05) - Full Research Report (PDF)

Bayesian Estimation Methods for Multidimensional Models for Discrete and Continuous Responses with a Structure on the Item and Person Parameters (RR 07-03)
by Cees A. W. Glas and Oksana Korobko, University of Twente, Enschede, The Netherlands

• Bayesian Estimation Methods for Multidimensional Models for Discrete and Continuous Responses with a Structure on the Item and Person Parameters (RR 07-03) - Executive Summary
• Bayesian Estimation Methods for Multidimensional Models for Discrete and Continuous Responses with a Structure on the Item and Person Parameters (RR 07-03) - Full Research Report (PDF)

A Bivariate Lognormal Response-Time Model for the Detection of Collusion Between Test Takers (RR 08-06)
by Wim J. van der Linden, University of Twente, Enschede, The Netherlands

• A Bivariate Lognormal Response-Time Model for the Detection of Collusion Between Test Takers (RR 08-06) - Executive Summary
• A Bivariate Lognormal Response-Time Model for the Detection of Collusion Between Test Takers (RR 08-06) - Full Research Report (PDF)

Comparability of Test-Taker Proficiency Scores on Computer Adaptive Tests Using Real and Simulated Data (RR 11-04)
by Josiah Evans, Law School Admisison Council; Jimmy de la Torre, Rutgers University; and Peter J. Pashley, Law School Admission Council

• Comparability of Test-Taker Proficiency Scores on Computer Adaptive Tests Using Real and Simulated Data (RR 11-04) - Executive Summary
• Comparability of Test-Taker Proficiency Scores on Computer Adaptive Tests Using Real and Simulated Data (RR 11-04) - Full Research Report (PDF)

Conceptual Issues in Response-Time Modeling (RR 08-01)
by Wim J. van der Linden, University of Twente, Enschede, The Netherlands

• Conceptual Issues in Response-Time Modeling (RR 08-01) - Executive Summary
• Conceptual Issues in Response-Time Modeling (RR 08-01) - Full Research Report (PDF)

Detection of Answer Copying via Kullback–Leibler Divergence and K-Index (RR 09-01)
by Dmitry I. Belov, Law School Admission Council; and Ronald D. Armstrong, Rutgers University

• Detection of Answer Copying via Kullback–Leibler Divergence and K-Index (RR 09-01) - Executive Summary
• Detection of Answer Copying via Kullback–Leibler Divergence and K-Index (RR 09-01) - Full Research Report (PDF)

Distributions of Kullback–Leibler Divergence and Its Application for the LSAT (RR 09-02)
by Dmitry I. Belov, Law School Admission Council; and Ronald D. Armstrong, Rutgers University

• Distributions of Kullback–Leibler Divergence and Its Application for the LSAT (RR 09-02) - Executive Summary
• Distributions of Kullback–Leibler Divergence and Its Application for the LSAT (RR 09-02) - Full Research Report (PDF)

Estimating and Testing the Extended Testlet Model (RR 12-03)
by Cees A. W. Glas, University of Twente, Enschede, The Netherlands

• Estimating and Testing the Extended Testlet Model (RR 12-03) - Executive Summary
• Estimating and Testing the Extended Testlet Model (RR 12-03) - Full Research Report (PDF)

Fit to Testlet Models and Differential Testlet Functioning (RR 12-07)
by Cees A. W. Glas, University of Twente, Enschede, The Netherlands

• Fit to Testlet Models and Differential Testlet Functioning (RR 12-07) - Executive Summary
• Fit to Testlet Models and Differential Testlet Functioning (RR 12-07) - Full Research Report (PDF)

A Hierarchical Framework for Modeling Speed and Accuracy on Test Items (RR 05-02)
by Wim J. van der Linden, University of Twente, Enschede, The Netherlands

• A Hierarchical Framework for Modeling Speed and Accuracy on Test Items (RR 05-02) - Executive Summary
• A Hierarchical Framework for Modeling Speed and Accuracy on Test Items (RR 05-02) - Full Research Report (PDF)

Identifying Critical Testlet Features Using Tree-Based Regression: An Illustration With the Analytical Reasoning Section of the LSAT (RR 12-04)
by Muirne C. S. Paap, Qiwei He, and Bernard P. Veldkamp, University of Twente, Enschede, The Netherlands

• Identifying Critical Testlet Features Using Tree-Based Regression: An Illustration With the Analytical Reasoning Section of the LSAT (RR 12-04) - Executive Summary
• Identifying Critical Testlet Features Using Tree-Based Regression: An Illustration With the Analytical Reasoning Section of the LSAT (RR 07-05) - Full Research Report (PDF)

Information-Based Versus Number-Correct Routing in Multistage Classification Tests (RR 07-05)
by Alexander Weissman and Dmitry I. Belov, Law School Admission Council; and Ronald D. Armstrong, Rutgers University

• Information-Based Versus Number-Correct Routing in Multistage Classification Tests (RR 07-05) - Executive Summary
• Information-Based Versus Number-Correct Routing in Multistage Classification Tests (RR 07-05) - Full Research Report (PDF)

Item Response Theory Parameter Estimation with Response Times as Collateral Information (RR 06-04)
by Wim J. van der Linden, Rinke H. Klein Entink, and Jean-Paul Fox, University of Twente, Enschede, The Netherlands

• Item Response Theory Parameter Estimation with Response Times as Collateral Information (RR 06-04) - Executive Summary
• Item Response Theory Parameter Estimation with Response Times as Collateral Information (RR 06-04) - Full Research Report (PDF)

Likelihood-based Estimation Methods for Models for Concurrent Continuous and Discrete Responses (RR 05-04)
by Cees A. W. Glas and Wim J. van der Linden, University of Twente, Enschede, The Netherlands

• Likelihood-based Estimation Methods for Models for Concurrent Continuous and Discrete Responses (RR 05-04) - Executive Summary
• Likelihood-based Estimation Methods for Models for Concurrent Continuous and Discrete Responses (RR 05-04) - Full Research Report (PDF)

Likelihood-Based Estimation Methods for Models for Concurrent Continuous and Discrete Responses With a Structure for the Item and Person Parameters (RR 06-03)
by Wim J. van der Linden and Cees A. W. Glas, University of Twente, Enschede, The Netherlands

• Likelihood-Based Estimation Methods for Models for Concurrent Continuous and Discrete Responses With a Structure for the Item and Person Parameters (RR 06-03)- Executive Summary
• Likelihood-Based Estimation Methods for Models for Concurrent Continuous and Discrete Responses With a Structure for the Item and Person Parameters (RR 06-03) - Full Research Report (PDF)

Likelihood-based Statistics for Continuous and Discrete Responses With a Structure for the Item and Person Parameters (RR 06-06)
by Cees A. W. Glas and Wim J. van der Linden, University of Twente, Enschede, The Netherlands

• Likelihood-based Statistics for Continuous and Discrete Responses With a Structure for the Item and Person Parameters (RR 06-06) - Executive Summary
• Likelihood-based Statistics for Continuous and Discrete Responses With a Structure for the Item and Person Parameters (RR 06-06) - Full Research Report (PDF)

Likelihood-based Statistics for Validating Continuous Response Models (RR 05-03)
by Cees A. W. Glas and Oksana Korobko, University of Twente, Enschede, The Netherlands

• Likelihood-based Statistics for Validating Continuous Response Models (RR 05-03) - Executive Summary
• Likelihood-based Statistics for Validating Continuous Response Models (RR 05-03) - Full Research Report (PDF)

Linking Response-Time Parameters Onto a Common Scale (RR 08-02)
by Wim J. van der Linden, University of Twente, Enschede, The Netherlands

• Linking Response-Time Parameters Onto a Common Scale (RR 08-02) - Executive Summary
• Linking Response-Time Parameters Onto a Common Scale (RR 08-02) - Full Research Report (PDF)

LSAT Listening Assessment: Theoretical Background and Specifications (RR 03-02)
by Kenneth Olson

• LSAT Listening Assessment: Theoretical Background and Specifications (RR 03-02) - Executive Summary
• LSAT Listening Assessment: Theoretical Background and Specifications (RR 03-02) - Full Research Report (PDF)

Optimizing Information Using the Expectation-Maximization Algorithm in Item Response Theory (RR 11-01)
by Alexander Weissman

• Optimizing Information Using the Expectation-Maximization Algorithm in Item Response Theory (RR 11-01) - Executive Summary
• Optimizing Information Using the Expectation-Maximization Algorithm in Item Response Theory (RR 11-01) - Full Research Report (PDF)

Predictive Control of Speededness in Adaptive Testing (RR 07-02)
by Wim J. van der Linden, University of Twente, Enschede, The Netherlands

• Predictive Control of Speededness in Adaptive Testing (RR 07-02) - Executive Summary
• Predictive Control of Speededness in Adaptive Testing (RR 07-02) - Full Research Report (PDF)

A Report on the Inclusion of Diverse Speakers on the LSAT Listening Comprehension Assessment: A Survey of the Literature with Recommendations (RR 04-02)
by Stephanie M. Strassel, University of Pennsylvania

• A Report on the Inclusion of Diverse Speakers on the LSAT Listening Comprehension Assessment: A Survey of the Literature with Recommendations (RR 04-02) - Executive Summary
• A Report on the Inclusion of Diverse Speakers on the LSAT Listening Comprehension Assessment: A Survey of the Literature with Recommendations (RR 04-02) - Full Research Report (PDF)

The Road to Law School and Beyond: Examining Challenges to Racial and Ethnic Diversity in the Legal Profession (RR 02-01)
by Gita Z. Wilder

• The Road to Law School and Beyond: Examining Challenges to Racial and Ethnic Diversity in the Legal Profession (RR 02-01) - Executive Summary
• The Road to Law School and Beyond: Examining Challenges to Racial and Ethnic Diversity in the Legal Profession (RR 02-01) - Full Research Report (PDF)

Sequencing an Adaptive Test Battery (RR 08-05)
by Wim J. van der Linden, University of Twente, Enschede, The Netherlands

• Sequencing an Adaptive Test Battery (RR 08-05) - Executive Summary
• Sequencing an Adaptive Test Battery (RR 08-05) - Full Research Report (PDF)

Statistical Algorithms for Detection of Test Collusion (RR 11-03)
by Dmitry I. Belov

• Statistical Algorithms for Detection of Test Collusion (RR 11-03) - Executive Summary
• Statistical Algorithms for Detection of Test Collusion (RR 11-03) - Full Research Report (PDF)

Statistical Tests for Conditional Independence in a Hierarchical Model for Speed and Accuracy on Test Items (RR 06-02)
by Wim J. van der Linden and Cees A. W. Glas, University of Twente, Enschede, The Netherlands

• Statistical Tests for Conditional Independence in a Hierarchical Model for Speed and Accuracy on Test Items (RR 06-02) - Executive Summary
• Statistical Tests for Conditional Independence in a Hierarchical Model for Speed and Accuracy on Test Items (RR 06-02) - Full Research Report (PDF)

A Stochastic Search for Test Assembly, Item Pool Analysis, and Design (RR 04-01)
by Dmitry Belov, Law School Admission Council; and Ronald D. Armstrong, Rutgers, The State University of New Jersey

• A Stochastic Search for Test Assembly, Item Pool Analysis, and Design (RR 04-01) - Executive Summary
• A Stochastic Search for Test Assembly, Item Pool Analysis, and Design (RR 04-01) - Full Research Report (PDF)

Structural Modeling Using Two-Step MML Procedures (RR 08-07)
by Cees A. W. Glas, University of Twente, Enschede, The Netherlands

• Structural Modeling Using Two-Step MML Procedures (RR 08-07) - Executive Summary
• Structural Modeling Using Two-Step MML Procedures (RR 08-07) - Full Research Report (PDF)

A Study of Structural Modeling Using Plausible Value Imputation (RR 08-03)
by Cees A. W. Glas and Hanneke Geerlings, University of Twente, Enschede, The Netherlands

• A Study of Structural Modeling Using Plausible Value Imputation (RR 08-03) - Executive Summary
• A Study of Structural Modeling Using Plausible Value Imputation (RR 08-03) - Full Research Report (PDF)

Test Design and Speededness (RR 07-01)
by Wim J. van der Linden, University of Twente, Enschede, The Netherlands

• Test Design and Speededness (RR 07-01) - Executive Summary
• Test Design and Speededness (RR 07-01) - Full Research Report (PDF)

Unraveling the Relationship Between Testlet Features and Item Parameters: An Empirical Example (RR 12-06)
by Muirne C. S. Paap and Bernard P. Veldkamp, University of Twente, Enschede, The Netherlands

•  Unraveling the Relationship Between Testlet Features and Item Parameters: An Empirical Example (RR 12-06) - Executive Summary
•  Unraveling the Relationship Between Testlet Features and Item Parameters: An Empirical Example (RR 12-06) - Full Research Report (PDF)

Using Response Times for Item Selection in Computerized Adaptive Testing (RR 06-01)
by Wim J. van der Linden, University of Twente, Enschede, The Netherlands

• Using Response Times for Item Selection in Computerized Adaptive Testing (RR 06-01) - Executive Summary
• Using Response Times for Item Selection in Computerized Adaptive Testing (RR 06-01) - Full Research Report (PDF)

Archived Research Reports

LSAC has archived all Research Reports that were published ten or more years ago. These reports are still available upon request.

• View Archived Research Reports (PDF)