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Goodness of fit test for general linear model with nonignorable missing on response variable

机译:响应变量缺失缺失缺失的一般线性模型的良好测试

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In this paper, we consider a general linear model where missing data occur in the response variable with a nonignorable mechanism. Also, to deal with missing data, we assume that the probability of missing data follows a logistic model. The main purpose of this paper is to construct some test functions to check the goodness of fit of the general linear model based on the score-type test. To achieve this aim, we use two appropriate estimating models and we construct two test functions based on these models. The asymptotic properties of the test functions are obtained under the null and the alternative hypotheses based on the estimated tilting parameter. The performances of the test functions are checked by some simulation studies. Also, these methods are used to check goodness of fit of the fitted models for real data.
机译:在本文中,我们考虑一种常规线性模型,其中缺失数据在响应变量中出现,具有不可能的机制。 此外,为了处理缺失的数据,我们假设缺失数据的概率遵循逻辑模型。 本文的主要目的是构建一些测试功能,以检查基于刻录型测试的通用线性模型的良好。 为实现此目的,我们使用两个适当的估计模型,并根据这些模型构建两个测试功能。 基于估计的倾斜参数,在NULL和替代假设下获得测试函数的渐近性质。 一些模拟研究检查了测试功能的性能。 此外,这些方法用于检查适合拟合模型的实际数据的良好。

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