Semiparametric Regression Analysis With Missing Response at Random

By Qihua Wang, Oliver B. Linton, Wolfgang Karl Härdle. 2003

252 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/3497d9a4e32c9bf1bc5cfc08ea48c7a3d8da8ddc

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Liugen Xue
2. Qihua Wang
3. I. Van Keilegom
4. Songxi Chen
5. Zhihua Sun
6. Bryan S. Graham
7. Jing Qin
8. Qihua Wang

In Statistics and Probability

1. I. Van Keilegom
2. Songxi Chen
3. Liugen Xue
4. Qihua Wang
5. Yousri Henchiri
6. Jun Shao
7. Biao Zhang
8. Jing Qin

Citations in the corpus

• A review on empirical likelihood methods for regression (2009, background): “See e.g. Qin and Jing (2001b) and Wang and Li (2002) for the analysis of the partial linear model.”
• Empirical likelihood for single-index varying-coefficient models (2012, background): “The related works are Wang and Rao [22], Wang, Linton and Härdle [21], Xue and Zhu [29–31], Zhu and Xue [32], Qin and Zhang [18], Stute, Xue and Zhu [20], Xue [27,28], Wang and Xue [23], among others.”
• Efficiency Bounds for Missing Data Models with Semiparametric Restrictions (2008, background): “Finally, the auxiliary restriction (5) ties down the conditional distribution of D given X and ensures Assumption 1.4 is satis ed.”
• Efficient and Doubly Robust Imputation for Covariate-Dependent Missing Responses (2008, methodology): “Because there is no continuous covariate in the group of individuals participating in the training program, for regression imputation, we need no nonparametric component, and thus the partially linear regression method of Wang et al. (2004) is the same as the Robins–Rotnitzky–Zhao method.”
• Regression imputation in the functional linear model with missing values in the response (2019, background): “Then, to impute a missing value, say Y` (where ` is a given integer between 1 and n), a simple way is to consider complete case analysis (see for instance [19, 7, 29, 22, 28]).”
• Estimation in partially linear models with missing responses at random (2007, methodology): “[21], where the methods are also competitive.”
• Empirical Likelihood for a Varying Coefficient Model With Longitudinal Data (2007, unknown): “…Chen (1993, 1994), Chen and Hall (1993), Chen and Qin (1993), Qin (1993), Qin and Lawless (1994), Li (1995), Li, Hollander, and McKeague (1996), Kitamura (1997), Wang and Rao (2002), Wang, Linton, and Härdle (2004), Xue and Zhu (2005, 2006), Zhu and Xue (2006), and Stute, Xue, and Zhu (2007).”