Abstract
Consider developing a regression model in a context where substantive theory is weak. Search procedures are often used to develop the equation: eg, fitting the equation, dropping insignificant variables, and refitting. As is well known, this can seriously distort the conventional goodness-of-fit statistics. Furthermore, the bootstrap and jackknife may not help in high-dimensional cases.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Achen, C. (1982). Interpreting and using regression. Beverly Hills, Calif.: Sage.
Baumrind, D. (1983). Specious causal attribution in the social sciences: the reformulated stepping-stone theory of heroin use as exemplar. J. Pers. Soc. Psych., 45, 1289–98.
Beran, R. (1984). Jackknife approximations to bootstrap estimates. Ann. Statist., 12, 101–118.
Bickel, P. and Freedman, D. (1981). Some asymptotic theory for the bootstrap. Ann. Statist., 9, 1196–1217.
Breiman, L. and Freedman, D. (1983). How many variables should be entered in a regression equation? J. Am. Stat. Assoc., 78, 131–136.
Daggett, R. and Freedman, D. (1985). Econometrics and the law: a case study in the proof of antitrust damages. In L. LeCam and R. Olshen (Eds.), Proceedings of the Berkeley Conference in Honor of Jerzy Neyman and Jack Kiefer, Vol I, 126–75. Belmont, Calif.: Wadsworth.
de Leeuw, J. (1985). Review of books by Long, Everitt, Saris and Stronkhorst. Psychometrika, 50, 371–5.
Eaton, M. and Freedman, D. (1982). A remark on adjusting for covariates in multiple regression. Technical Report No. 11, Department of Statistics, University of California, Berkeley.
Efron, B. (1979). Bootstrap methods: another look at the jackknife. Ann. Statist., 7, 1–26.
Efron, B. (1982). The Jackknife, the Bootstrap, and Other Resampling Plans. Philadelphia: SIAM.
Freedman, D. (1981a). Some pitfalls in large econometric models: a case study. J. Bus. 54, 479–500.
Freedman, D. (1981b). Bootstrapping regression models. Ann. Statist., 9, 1218–1228.
Freedman, D. (1983). A note on screening regression equations. Am. Stat., 37, 152–5.
Freedman, D. (1985). Statistics and the scientific method. In W. Mason and S. Fienberg (Eds.), Cohort Analysis in Social Research: Beyond the Identification Problem, 345–390 (with discussion). New York: Springer.
Freedman, D. (1986). As others see us: a case study in path analysis. Technical report, Department of Statistics, University of California, Berkeley. To appear in J. Ed. Stat..
Freedman, D. and Navidi, W. (1986). Regression models for adjusting the 1980 Census. Stat. Sci., 1, 1–39.
Freedman, D. and Peters, S. (1984a). Some notes on the bootstrap in regression problems. J. Bus. Econ. Stat., 2, 406–409.
Freedman, D. and Peters, S. (1984b). Bootstrapping a regression equation: some empirical results. J. Am. Stat. Assoc., 79, 97–106.
Freedman, D. and Peters, S. (1984c). Bootstrapping an econometric model: some empirical results. J. Bus. Econ. Stat., 2, 150–8.
Freedman, D. and Peters, S. (1985). Using the bootstrap to evaluate a forecasting equation. J. Forecasting, 4, 251–262.
Freedman, D., Rothenberg, T. & Sutch, R. (1983). On energy policy models. J. Bus. Econ. Stat., 1, 24–36. (With discussion.)
Gong, G. (1986). Cross-validation, the jackknife, and the bootstrap: excess error estimation in forward logistic regression. J. Am. Stat. Assoc., 81, 108–113.
Hendry, D. (1980). Econometrics — alchemy or science? Econometrica, 7, 387–406.
Leamer, E. (1983). Taking the con out of econometrics. Am. Econ. Rev., 73, 31–43.
Ling, R. (1983). Review of Correlation and Causation by Kenny. J. Am. Stat. Assoc., 77, 489–91.
Lovell, M. (1983). Data mining. Rev. Econ. Statist., LXV, 1–11.
McNees, S.K. (1986). Forecasting accuracy of alternative techniques: a comparison of US macroeconomic forecasts. J. Bus. Econ. Stat., 4, 5–24. (With discussion.)
Theil, H. (1971). Principles of Econometrics. New York: Wiley.
Zarnowitz, V. (1979). An analysis of annual and multiperiod quarterly forecasts of aggregate income, output, and the price level. J. Bus., 52, 1–34.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 1988 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Freedman, D.A., Navidi, W., Peters, S.C. (1988). On the Impact of Variable Selection in Fitting Regression Equations. In: Dijkstra, T.K. (eds) On Model Uncertainty and its Statistical Implications. Lecture Notes in Economics and Mathematical Systems, vol 307. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-61564-1_1
Download citation
DOI: https://doi.org/10.1007/978-3-642-61564-1_1
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-19367-8
Online ISBN: 978-3-642-61564-1
eBook Packages: Springer Book Archive