A solution to control for nonresponse bias consists of multiplying the design weights of respondents by the inverse of estimated response probabilities to compensate for the nonrespondents. Maximum likelihood and calibration are two approaches that can be applied to obtain estimated response probabilities. The paper develops asymptotic properties of the resulting estimator when calibration is applied. A logistic regression model for the response probabilities is postulated and missing at random data is supposed. The author shows that the estimators with the response probabilities estimated via calibration are asymptotically equivalent to unbiased estimators and that a gain in efficiency is obtained when estimating the response probabilities via calibration as compared to the estimator with the true response probabilities.

翻译：控制不答复偏差的解决方案包括将答复者的设计权重乘以估计反应概率的反比乘以估计反应概率来补偿不答复者。最大可能性和校准是两种方法,可用于获取估计反应概率。本文在校准应用时开发了由此得出的估计值的无反应性属性。假设了反应概率的后勤回归模型,并随机数据缺失。作者显示,通过校准估计反应概率的估算值与公正的估计值相仿,在通过校准估计值与真实反应概率的估测值相比估计反应概率时,效率得到提高。