Regression Analysis for Categorical Variables With Outcome Subject to Nonignorable Nonresponse
针对分类结果变量存在不可忽略无回答的情况，提出一种对数线性模型，重点解决回归设定下的估计与假设检验问题，并给出参数边界解的存在性及置信区间构建方法。
Abstract We develop a log-linear model for categorical response subject to nonignorable nonresponse. The paper differs from Fay (1986) in its focus on estimation and hypothesis testing in a regression setting, as opposed to imputation in a multivariate setting. We present several new results concerning the existence of solutions on the boundary of the parameter space and the construction of confidence intervals for estimates. We illustrate the method by estimating the proportion of voters preferring Truman in a 1948 preelection poll (Mosteller, Hyman, McCarthy, Marks, and Truman 1949). Results may depend strongly on the model assumed for nonresponse; goodness-of-fit tests are available for comparing alternative models.