Calculating Standard Errors of Predicted Values Based on Nonlinear Functional Forms

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Calculating Standard Errors of Predicted Values Based on Nonlinear Functional Forms

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dc.contributor.author King, Gary
dc.date.accessioned 2010-08-04T14:41:32Z
dc.date.issued 1991
dc.identifier.citation King, Gary. 1991. Calculating standard errors of predicted values based on nonlinear functional forms. The Political Methodologist 4(2): 2-4. en_US
dc.identifier.uri http://nrs.harvard.edu/urn-3:HUL.InstRepos:4323918
dc.description.abstract Whenever we report predicted values, we should also report some measure of the uncertainty of these estimates. In the linear case, this is relatively simple, and the answer well-known, but with nonlinear models the answer may not be apparent. This short article shows how to make these calculations. I first present this for the familiar linear case, also reviewing the two forms of uncertainty in these estimates, and then show how to calculate these for any arbitrary function. An example appears last. en_US
dc.description.sponsorship Government en_US
dc.language.iso en_US en_US
dc.publisher The Society for Political Methodology en_US
dc.relation.isversionof http://polmeth.wustl.edu/index.php en_US
dc.relation.hasversion http://polmeth.wustl.edu/methodologist/tpm_v4_n2.pdf en_US
dash.license LAA
dc.title Calculating Standard Errors of Predicted Values Based on Nonlinear Functional Forms en_US
dc.type Journal Article en_US
dc.description.version Version of Record en_US
dc.relation.journal The Political Methodologist en_US
dash.depositing.author King, Gary
dc.date.available 2010-08-04T14:41:32Z

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  • FAS Scholarly Articles [7078]
    Peer reviewed scholarly articles from the Faculty of Arts and Sciences of Harvard University

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