SPECIFICATION ERROR IN MULTINOMIAL LOGIT-MODELS - ANALYSIS OF THE OMITTED VARIABLE BIAS
SPECIFICATION ERROR IN MULTINOMIAL LOGIT-MODELS - ANALYSIS OF THE OMITTED VARIABLE BIAS
复制标题
DOI：
10.1016/0304-4076(82)90019-7
复制
发表时间：
1982-01-01
影响因子：
6.3
通讯作者：
LEE, LF
中科院分区：
文献类型：
--
作者：
LEE, LF
本文分析了多项逻辑斯谛概率模型中的遗漏变量偏差问题。充分的，以及必要的，条件下，省略的变量将不会创建渐近有偏的系数估计所包含的变量推导出来。在反应变量的条件下，如果省略的解释变量和包含的解释变量是独立的，则偏倚不会发生。如果省略的相关变量与包含的解释变量无关，则会发生偏倚。所包含变量的系数在偏倚的方向上起着重要的作用。
In this article, we analyze the omitted variable bias problem in the multinomial logistic probability model. Sufficient, as well as necessary, conditions under which the omitted variable will not create asymptotically biased coefficient estimates for the included variables are derived. Conditional on the response variable, if the omitted explanatory and the included explanatory variable are independent, the bias will not occur. Bias will occur if the omitted relevant variable is independent with the included explanatory variable. The coefficient of the included variable plays an important role in the direction of the bias.