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

Abstract

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.