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Confidence intervals for predicted outcomes in regression models for categorical outcomes

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Author Info
Jun Xu (Indiana University)
J. Scott Long (Indiana University)
Abstract

We discuss methods for computing confidence intervals for predictions and discrete changes in predictions for regression models for categorical outcomes. The methods include endpoint transformation, the delta method, and bootstrap- ping. We also describe an update to prvalue and prgen from the SPost package, which adds the ability to compute confidence intervals. The article provides several examples that illustrate the application of these methods. Copyright 2005 by StataCorp LP.

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Publisher Info
Article provided by StataCorp LP in its journal Stata Journal.

Volume (Year): 5 (2005)
Issue (Month): 4 (December)
Pages: 537-559
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Handle: RePEc:tsj:stataj:v:5:y:2005:i:4:p:537-559

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Related research
Keywords: prvalue; prgen; confidence interval; predicted probability; dis- crete choice models; endpoint transformation; delta method; bootstrap;

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  1. J. Scott Long, 2006. "Group comparisons and other issues in interpreting models for categorical outcomes using Stata," North American Stata Users' Group Meetings 2006 15, Stata Users Group. [Downloadable!]
  2. Reiner Martin & Ludger Schuknecht & Isabel Vansteenkiste, 2007. "The role of the exchange rate for adjustment in Boom and Bust episodes," Working Paper Series 813, European Central Bank. [Downloadable!]
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This page was last updated on 2009-12-10.


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