, Volume 52, Issue 2, pp 275–291 | Cite as

A comparison of the efficiency and accuracy of BILOG and LOGIST

  • Wendy M. Yen
Computational Psychometrics


Comparisons are made between BILOG version 2.2 and LOGIST 5.0 Version 2.5 in estimating the item parameters, traits, item characteristic functions (ICFs), and test characteristic functions (TCFs) for the three-parameter logistic model. Data analyzed are simulated item responses for 1000 simulees and one 10-item test, four 20-item tests, and four 40-item tests. LOGIST usually was faster than BILOG in producing maximum likelihood estimates. BILOG almost always produced more accurate estimates of individual item parameters. In estimating ICFs and TCFs BILOG was more accurate for the 10-item test, and the two programs were about equally accurate for the 20- and 40-item tests.

Key words

BILOG computer program item response theory LOGIST tests 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Bock, R. D., & Aitkin, M. (1981). Marginal maximum likelihood estimation of item parameters: Application of an EM algorithm.Psychometrika, 46, 443–459.Google Scholar
  2. Hulin, C. L., Lissak, R. I., & Drasgow, F. (1982). Recovery of two- and three-parameter logistic item characteristic curves: A Monte Carlo study.Applied Psychological Measurement, 6, 249–260.Google Scholar
  3. Lord, F. M. (1969). Estimating true-score distributions in psychological testing (An empirical Bayes estimation problem).Psychometrika, 34, 259–299.Google Scholar
  4. Lord, F. M. (1974). Estimation of latent ability and item parameters when there are omitted responses.Psychometrika, 39, 247–264.Google Scholar
  5. Lord, F. M. (1975). The “ability” scale in item characteristic curve theory.Psychometrika, 40, 205–217.Google Scholar
  6. Lord, F. M. (1983a). Statistical bias in maximum likelihood estimators of item parameters.Psychometrika, 48, 425–435.Google Scholar
  7. Lord, F. M. (1983b). Unbiased estimators of ability parameters, of their variance, and of their parallel-forms reliability.Psychometrika, 48, 233–245.Google Scholar
  8. Lord, F. M. (1984).Maximum likelihood and Bayesian parameter estimates in item response theory (RR-84-30-ONR). Princeton, NJ: Educational Testing Service.Google Scholar
  9. Mislevy, R. J. (1984). Estimating latent distributions.Psychometrika, 49, 359–381.Google Scholar
  10. Mislevy, R. J., & Bock, R. D. (1984).BILOG Version 2.2.: Item analysis and test scoring with binary logistic models. Mooresville, IN: Scientific Software.Google Scholar
  11. Qualls, A. L., & Ansley, T. N. (1985, April).A comparison of item and ability parameter estimates derived from LOGIST and BILOG. Paper presented at the meeting of the National Council on Measurement in Education, Chicago, IL.Google Scholar
  12. Stocking, M. L., & Lord, F. M. (1983). Developing a common metric in item response theory.Applied Psychological Measurement, 7, 201–210.Google Scholar
  13. Wingersky, M. S. (1983). LOGIST: A program for computing maximum likelihood procedures for logistic test models. In R. K. Hambleton (Ed.),Applications of item response theory (pp. 45–56). British Columbia: Educational Research Institute of British Columbia.Google Scholar
  14. Wingersky, M. S., Barton, M. A., & Lord, F. M. (1982)LOGIST 5.0 version 1.0 users' guide. Princeton, NJ: Educational Testing Service. (Version 2.5 updated 1984).Google Scholar
  15. Wingersky, M. S., & Lord, F. M. (1973).A computer program for estimating examinee ability and item characteristic curve parameters when there are omitted responses (RM-73-2). Princeton, NJ: Educational Testing Service.Google Scholar
  16. Yen, W. M. (1983). Tau equivalence and equipercentile equating.Psychometrika, 48, 353–369.Google Scholar
  17. Yen, W. M. (1984). Obtaining maximum likelihood trait estimates from number-correct scores for the three-parameter logistic model.Journal of Educational Measurement, 21, 93–111.Google Scholar
  18. Yen, W. M. (1985). Increasing item complexity: A possible cause of scale shrinkage for unidimensional item response theory.Psychometrika, 50, 399–410.Google Scholar

Copyright information

© The Psychometric Society 1987

Authors and Affiliations

  • Wendy M. Yen
    • 1
  1. 1.CTB/McGraw-HillMonterey

Personalised recommendations