Regression models for categorical dependent variables using Stata

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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 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.

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Document Metadata

Issuer: SAGE Publications
Document Type: Research / Academic Paper
Publication Year: 2006
Retrieved: 5 May 2026
Source: Contact XFID for Access
Record ID: XFMUBLYK3T
Validation: Inferred by XFID

Topics

Econometrics

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SAGE Publications (2006). Regression models for categorical dependent variables using Stata. XFID: XF-MUBLYK3-T. Retrieved from https://xframework.id/XFMUBLYK3T

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