You are not currently logged in.
Access JSTOR through your library or other institution:
If You Use a Screen ReaderThis content is available through Read Online (Free) program, which relies on page scans. Since scans are not currently available to screen readers, please contact JSTOR User Support for access. We'll provide a PDF copy for your screen reader.
Model Selection: An Integral Part of Inference
S. T. Buckland, K. P. Burnham and N. H. Augustin
Vol. 53, No. 2 (Jun., 1997), pp. 603-618
Published by: International Biometric Society
Stable URL: http://www.jstor.org/stable/2533961
Page Count: 16
You can always find the topics here!Topics: Modeling, Statistical models, Inference, Parametric models, Statistical estimation, Simulations, Statistics, Confidence interval, Analytical estimating, Estimation methods
Were these topics helpful?See something inaccurate? Let us know!
Select the topics that are inaccurate.
Since scans are not currently available to screen readers, please contact JSTOR User Support for access. We'll provide a PDF copy for your screen reader.
Preview not available
We argue that model selection uncertainty should be fully incorporated into statistical inference whenever estimation is sensitive to model choice and that choice is made with reference to the data. We consider different philosophies for achieving this goal and suggest strategies for data analysis. We illustrate our methods through three examples. The first is a Poisson regression of bird counts in which a choice is to be made between inclusion of one or both of two covariates. The second is a line transect data set for which different models yield substantially different estimates of abundance. The third is a simulated example in which truth is known.
Biometrics © 1997 International Biometric Society