THE BIAS OF ESTIMATING EQUATIONS WITH APPLICATION TO THE ERROR RATE OF LOGISTIC DISCRIMINATION

• 成果类型: Article
• 署名作者: ONEILL, TJ
• 署名单位: Australian National University
• 刊物名称: JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
• ISSN/ISSBN: 0162-1459
• 发表日期: 1994
• 页码: 1492-1498
• 关键词: fisher

摘要

The logistic regression classification method uses parameter estimates that are the solution of an estimating equation. This article derives a convenient expression for the bias of a vector estimator defined by estimating equations. The expression and the results of O'Neill are used to derive the bias and the error or misclassification rate of logistic regression classification in two examples where the assumed model for logistic regression does not hold. Logistic regression classification is found to be very robust for the departures considered.