罗伊特
统计
计量经济学
有序概率单位
残余物
普罗比特
逻辑回归
Probit模型
数学
变化(天文学)
有序逻辑
学生化残差
算法
天体物理学
物理
标识
DOI:10.1177/0049124199028002003
摘要
In logit and probit regression analysis, a common practice is to estimate separate models for two or more groups and then compare coefficients across groups. An equivalent method is to test for interactions between particular predictors and dummy (indicator) variables representing the groups. Both methods may lead to invalid conclusions if residual variation differs across groups. New tests are proposed that adjust for unequal residual variation.
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