Abstract
Model checking for the general linear regression model with nonignorable missing response is studied. Based on an exponential tilting model, two estimators are proposed for the unknown parameter in the regression model. Then, two empirical-process-based tests are constructed. The asymptotic properties of the proposed tests are investigated under the null and local alternative hypotheses in different scenarios. It is found that the two tests perform identically in the asymptotic sense. In addition, a nonparametric Monte Carlo test procedure is performed to obtain the critical values. Further, simulation studies are conducted to assess the performance of the proposed tests and compare them with other possible approaches. Finally, a real data set is analyzed for illustration.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 1-12 |
| Number of pages | 12 |
| Journal | Computational Statistics and Data Analysis |
| Volume | 138 |
| DOIs | |
| State | Published - Oct 2019 |
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All Science Journal Classification (ASJC) codes
- Statistics and Probability
- Computational Mathematics
- Computational Theory and Mathematics
- Applied Mathematics
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Model checking for general linear regression with nonignorable missing response. / Guo, Xu; Song, Lianlian; Fang, Yun; Zhu, Lixing.
In: Computational Statistics and Data Analysis, Vol. 138, 10.2019, p. 1-12.Research output: Contribution to journal › Article
TY - JOUR
T1 - Model checking for general linear regression with nonignorable missing response
AU - Guo, Xu
AU - Song, Lianlian
AU - Fang, Yun
AU - Zhu, Lixing
PY - 2019/10
Y1 - 2019/10
N2 - Model checking for the general linear regression model with nonignorable missing response is studied. Based on an exponential tilting model, two estimators are proposed for the unknown parameter in the regression model. Then, two empirical-process-based tests are constructed. The asymptotic properties of the proposed tests are investigated under the null and local alternative hypotheses in different scenarios. It is found that the two tests perform identically in the asymptotic sense. In addition, a nonparametric Monte Carlo test procedure is performed to obtain the critical values. Further, simulation studies are conducted to assess the performance of the proposed tests and compare them with other possible approaches. Finally, a real data set is analyzed for illustration.
AB - Model checking for the general linear regression model with nonignorable missing response is studied. Based on an exponential tilting model, two estimators are proposed for the unknown parameter in the regression model. Then, two empirical-process-based tests are constructed. The asymptotic properties of the proposed tests are investigated under the null and local alternative hypotheses in different scenarios. It is found that the two tests perform identically in the asymptotic sense. In addition, a nonparametric Monte Carlo test procedure is performed to obtain the critical values. Further, simulation studies are conducted to assess the performance of the proposed tests and compare them with other possible approaches. Finally, a real data set is analyzed for illustration.
UR - http://www.scopus.com/inward/record.url?scp=85063759783&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85063759783&partnerID=8YFLogxK
U2 - 10.1016/j.csda.2019.03.009
DO - 10.1016/j.csda.2019.03.009
M3 - Article
AN - SCOPUS:85063759783
VL - 138
SP - 1
EP - 12
JO - Computational Statistics and Data Analysis
JF - Computational Statistics and Data Analysis
SN - 0167-9473
ER -