### Abstract

Original language | Undefined |
---|---|

Place of Publication | Enschede, the Netherlands |

Publisher | University of Twente, Faculty Educational Science and Technology |

Publication status | Published - 1997 |

### Publication series

Name | OMD research report |
---|---|

Publisher | University of Twente, Faculty of Educational Science and Technology |

No. | 97-02 |

### Keywords

- Ability
- Adaptive Testing
- IR-103604
- Item Response Theory
- Test Construction
- Computer Assisted Testing
- Foreign Countries
- Algorithms

### Cite this

*A procedure for empirical initialization of adaptive testing algorithms*. (OMD research report; No. 97-02). Enschede, the Netherlands: University of Twente, Faculty Educational Science and Technology.

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*A procedure for empirical initialization of adaptive testing algorithms*. OMD research report, no. 97-02, University of Twente, Faculty Educational Science and Technology, Enschede, the Netherlands.

**A procedure for empirical initialization of adaptive testing algorithms.** / van der Linden, Willem J.

Research output: Book/Report › Report › Other research output

TY - BOOK

T1 - A procedure for empirical initialization of adaptive testing algorithms

AU - van der Linden, Willem J.

PY - 1997

Y1 - 1997

N2 - In constrained adaptive testing, the numbers of constraints needed to control the content of the tests can easily run into the hundreds. Proper initialization of the algorithm becomes a requirement because the presence of large numbers of constraints slows down the convergence of the ability estimator. In this paper, an empirical initialization of the algorithm is proposed based on the statistical relation between the ability variable and background variables known prior to the test. The relation is modeled using a two-parameter logistic version of an item response theory (IRT) model with manifest predictors discussed in A.H. Zwinderman (1991). An empirical example shows how an (incomplete) sample of response data and data on background variables can be used to derive an initial ability estimate or an empirical prior distribution for the ability parameter. An appendix gives the derivation of an equation for the estimator.

AB - In constrained adaptive testing, the numbers of constraints needed to control the content of the tests can easily run into the hundreds. Proper initialization of the algorithm becomes a requirement because the presence of large numbers of constraints slows down the convergence of the ability estimator. In this paper, an empirical initialization of the algorithm is proposed based on the statistical relation between the ability variable and background variables known prior to the test. The relation is modeled using a two-parameter logistic version of an item response theory (IRT) model with manifest predictors discussed in A.H. Zwinderman (1991). An empirical example shows how an (incomplete) sample of response data and data on background variables can be used to derive an initial ability estimate or an empirical prior distribution for the ability parameter. An appendix gives the derivation of an equation for the estimator.

KW - Ability

KW - Adaptive Testing

KW - IR-103604

KW - Item Response Theory

KW - Test Construction

KW - Computer Assisted Testing

KW - Foreign Countries

KW - Algorithms

M3 - Report

T3 - OMD research report

BT - A procedure for empirical initialization of adaptive testing algorithms

PB - University of Twente, Faculty Educational Science and Technology

CY - Enschede, the Netherlands

ER -