What makes improper linear models tick?

Rationality and Social Responsibility: Essays in Honor of Robyn Mason Dawes

Volumn , Issue , 2008, Pages 71-89

  Dana, Jason ^a  

^a UNIVERSITY OF PENNSYLVANIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 77956061865     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.4324/9780203889695     Document Type: Chapter

References (25)

1. American Lung Association. (2005). Facts about lung cancer. Retrieved from http://www.lungusa.org/site/pp.asp?c=dvLUK9O0E&b=35427
2. Brown, P. J. (1993). Measurement, regression, and calibration. London: Oxford University Press.
3. Casella, G. (1985). Condition numbers and minimax ridge-regression estimators. Journal of the American Statistical Association, 80, 753-758.
4. Centers for Disease Control. (2005). Early release of selected estimates based on data from the 2004 National Health Interview Survey. Retrieved from http://www.cdc.gov/nchs/data/nhis/earlyrelease/200506_08.pdf
5. Cohen, J. (1990). Things I have learned (so far). American Psychologist, 45, 1304-1312.
6. Dana, J., & Dawes, R. (2004). The superiority of simple alternatives to regression for social science predictions. Journal of Educational and Behavioral Statistics, 29, 317-331.
7. Dawes, R. (1971). A case study of graduate admissions: Application of three principles of human decision making. American Psychologist, 26, 180-188.
8. Dawes, R. (1979). The robust beauty of improper linear models in decision making. American Psychologist, 34, 571-582.
9. Dawes, R., & Corrigan, B. (1974). Linear models in decision making. Psychological Bulletin, 81, 95-106.
10. Edwards, W. (1976). Comment on "Equal weighting in multi-attribute models:A rationale, an example, and some extensions" by Hillel Einhorn. In M. Schiff & G. Sorter (Eds.), Proceedings of the Conference on Topical Research in Accounting (np). New York: New York University Press.
11. Einhorn, H. J. & Hogarth, R. M. (1975). Unit weighting schemes for decision making. Organizational Behavior and Human Performance, 13, 171-192.
12. Einhorn, H. J. (1986). Accepting error to make less error. Journal of Personality Assessment, 50, 387-395.
13. Eldar, Y. C., Ben-Tal, A., & Nemirovski, A. (2005). Robust mean-squared error estimation in the presence of bounded data uncertainties. IEEE Transactions on Signal Processing, 53, 168-181.
14. Gardner, E. (1985). Exponential smoothing: the state of the art. Journal of Forecasting, 4, 1-38.
15. Gigerenzer, G., & Goldstein, D. G. (1996). Reasoning the fast and frugal way:Models of bounded rationality. Psychological Review, 103, 650-669.
16. Gigerenzer, G., & Todd, P. M. (1999). Simple heuristics that make us smart. Oxford, UK: Oxford University Press.
17. Green, B. F. (1977). Parameter sensitivity in multivariate methods. Multivariate Behavioral Research, 12, 263-288.
18. Hammond, K. R. (1996). Human judgment and social policy. New York: Oxford University Press.
19. Hoerl, A., & Kennard, R. (1970). Ridge regression: Biased estimation for nonorthogonal problems. Technometrics, 12, 55-67.
20. Hogarth, R., & Karelaia, N. (2005). Ignoring information in binary choice with continuous variables: When is less "more"? Journal of Mathematical Psychology, 49, 115-124.
21. James, W., & Stein, C. (1961). Estimation with quadratic loss. In Proceedings of the Fourth Berkeley Symposium on Mathematical Statistics and Probability (Vol. 1, pp. 361-379). Berkeley: University of California Press.
22. Meehl, P. E. (1954). Clinical vs. statistical prediction: A theoretical analysis and a review of the evidence. Minneapolis: University of Minnesota Press.
23. Muth, J. (1960). Optimal properties of exponentially weighted forecasts. Journal of the American Statistical Association, 55, 299-306.
24. Taagepera, R. (2005). Beyond regression: The need for logical models. Paper presented at the Third Conference of the Belgian Political Science Association. Retrieved from http://www.ut.ee/SORT/05k/kursused/Beyond.pdf
25. Wainer, H. (1976). Estimating coefficients in linear models: It don't make no nevermind. Psychological Bulletin. 83, 213-217.