Hierarchical logistic regression in course placement

Journal of Educational Measurement

Volumn 41, Issue 3, 2004, Pages 271-286

  Schulz, E Matthew ^a,d   Betebenner, Damian ^b   Ahn, Meeyeon ^c  

^a ACT INC   (United States)

^b BOSTON COLLEGE   (United States)

^c UNIVERSITY OF IOWA   (United States)

^d American College Testing Incorporated   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 6344270066     PISSN: 00220655     EISSN: None     Source Type: Journal    
DOI: 10.1111/j.1745-3984.2004.tb01166.x     Document Type: Article

References (35)

1. ACT, Inc. (1994). ACT Assessment Course Placement Service Interpretive Guide. Iowa City, IA: Author.
2. ACT, Inc. (1995). ASSET Course Placement Service Interpretive Guide. Iowa City, IA: Author.
3. Ben-Shakhar, G., & Beller, M. (1983). An application of a decision-theoretic model to a quota-free selection problem. Journal of Applied Psychology, 68, 137-146.
4. Braun, H. I., Jones, D. H., Rubin, D. B., & Thayer, D. T. (1983). Empirical Bayes estimation of coefficients in the general linear model from data of deficient rank. Psychometrika, 48(2), 171-181.
5. Bryk, A. S., & Raudenbush, S. W. (1992). Hierarchical linear models. Newbury Park: Sage Publications.
6. Cohen, J. (1960). A coefficient of agreement for nominal scales. Educational and Psychological Measurement, 20(1), 37-46.
7. Efron, B., & Morris, C. (1977). Stein's paradox in statistics. Scientific American, 236(5), 110, 121-127.
8. Gelman, A., Carlin, J. B., Stern, H. S., and Rubin, D. B. (1995). Bayesian data analysis. New York: Chapman & Hall.
9. Gelman, A., & Rubin, D. B. (1992). Inference from iterative simulation using multiple sequences (with discussion). Statistical Science, 7, 457-511.
10. Goodman, L. A., & Kruskal, W. H. (1954). Measures of association for cross-classifications. Journal of the American Statistical Association, 49, 732-764.
11. Gross, A. L., & Su, W. H., (1975). Defining a "fair" or "unbiased" selection model: A question of utilities. Journal of Applied Psychology, 60, 345-351.
12. Hosmer, D. W., & Lemeshow, S. (2000). Applied logistic regression (2nd ed.). New York: John Wiley & Sons, Inc.
13. Houston, W. M., & Sawyer, R. (1988). Central prediction systems for predicting specific course grades. ACT Research Report Series 88-4. Iowa City, IA: ACT, Inc.
14. Houston, W. M., & Woodruff, D. J. (1997). Empirical Bayes estimates of parameters from the logistic regression model. ACT Research Report Series 97-6. Iowa City, IA: ACT, Inc.
15. Kelly, T. L. (1927). The interpretation of educational measurements. New York: World Books.
16. Lindley, D. V., & Smith, A. F. M. (1972). Bayes estimates for the linear model. Journal of the Royal Statistical Society, Series B, 34, 1-41.
17. Morris, C. N. (1983). Parametric empirical Bayes inference: Theory and applications. Journal of the American Statistical Association, 78(381), 47-55.
18. Nebebe, F., & Stroud, T. W. F. (1988). Bayes and empirical Bayes shrinkage estimation of regression coefficients: A cross-validation study. Journal of Educational Statistics, 13(3), 199-213.
19. Nichols, J. L., Orehovec, P. M., & Ingold, S. (1999). Using logistic regression to identify new "At-Risk" freshmen. Journal of Marketing for Higher Education, 9, 25-37.
20. Novick, M. R., & Jackson, P. H. (1974). Further cross-validation analysis of the Bayesian m-group regression method. American Educational Research Journal, 11(1), 77-85.
21. Novick, M. R., Jackson, P. H., Thayer, D. T., & Cole, N. S. (1972). Estimating multiple regressions in m groups: A cross-validation study. British Journal of Mathematical and Statistical Psychology, 25, 33-50.
22. Petersen, N. S. (1974). An expected utility model for "optimal" selection. Unpublished dissertation, University of Iowa, 1974.
23. Petersen, N. S. (1976). An expected utility model for "optimal" selection. Journal of Educational Statistics, 1, 333-358.
24. Petersen, N. S., & Novick, M. R. (1976). An evaluation of some models for culture-fair selection. Journal of Educational Measurement, 13, 3-29.
25. Raju, N. S., Steinhaus, S. D., Edwards, J. E., & DeLessio, J. (1991). A logistic regression model for personnel selection. Applied Psychological Measurement, 15, 139-152.
26. Raudenbush, S. W. (1988). Educational applications of hierarchical linear models: A review. Journal of Educational Statistics, 13(2), 85-116.
27. Raudenbush, S., Bryk, A., Cheong, Y. F., & Congdon, R. (2000). HLM 5 hierarchical and nonlinear modeling. Lincolnwood, IL: Scientific Software International, Inc.
28. Rubin, D. R. (1980). Using empirical Bayes techniques in the law school validity studies. Journal of the American Statistical Association, 75(372), 801-816.
29. SAS (1990). SAS/STAT User's guide, volume 2. Cary, NC: SAS Institute, Inc.
30. Sawyer, R. L. (1996). Decision theory models for validating course placement tests. Journal of Educational Measurement, 33, 271-290.
31. Schmidt, A. E. (2000). An approximation of a hierarchical logistic regression model to establish predictive validity of scores on a nursing licensure exam. Educational and Psychological Measurement, 60, 463-478.
32. Seltzer, M. H., Wong, W. H., & Bryk, A. S. (1996). Bayesian analysis in applications of hierarchical models: Issues and methods. Journal of Educational and Behavioral Statistics, 21, 131-167.
33. Spiegelhalter, D., Thomas, A., & Best, N. (2000, April). WinBUGS version 1.3 user manual. Cambridge; UK: Institute of Public Health, MRC Biostatistics Unit.
34. Stiratelli, R., Laird, N., & Ware, J. H. (1984). Random effects models for serial observations with binary response. Biometrics, 40, 961-971.
35. Wong, G. Y., & Mason, W. M. (1985). The hierarchical logistic regression model for multilevel analysis. Journal of the American Statistical Association, 80(391), 513-524.