Confidence intervals for predicted outcomes in regression models for categorical outcomes

dc.creatorXu, Jun
dc.creatorLong, J. Scott
dc.date2017-04-01T18:54:55Z
dc.date.accessioned2026-07-09T05:49:59Z
dc.descriptionWe 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 bootstrapping. 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.
dc.identifierOther:st0094
dc.identifierdoi:10.22004/ag.econ.117544
dc.identifierhttps://ageconsearch.umn.edu/record/117544/files/sjart_st0094.pdf
dc.identifierhttp://ageconsearch.umn.edu/record/117544
dc.identifier.urihttp://hdl.handle.net/123456789/568928
dc.languageeng
dc.publisher
dc.sourcehttp://ageconsearch.umn.edu/record/117544
dc.titleConfidence intervals for predicted outcomes in regression models for categorical outcomes
dc.typeText

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