Estimation With Survey Data Under Nonignorable Nonresponse or Informative Sampling

By Jing Qin, D. Leung, Jun Shao. 2002

141 citations recorded by the source corpus.

Subfields: Sociology and Political Science, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/74646821be3363f773cb2b158960472fcbddf5b5

How researchers see this paper

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

In Sociology and Political Science

1. Jae Kwang Kim
2. Jun Shao
3. Peng Ding
4. Zhi Geng
5. Sheng Wang
6. Biao Zhang
7. Wang Miao
8. Jing Qin

In Statistics and Probability

1. Peng Ding
2. Jae Kwang Kim
3. Zhi Geng
4. Wang Miao
5. Jun Shao
6. Biao Zhang
7. Sheng Wang
8. Jing Qin

Citations in the corpus

• Identifiability of Normal and Normal Mixture Models with Nonignorable Missing Data (2015, methodology): “Many researchers (e.g., Greenlees, Reece, and Zieschang 1982; Glynn, Laird, andRubin 1986; Rotnitzky andRobins 1997; Qin, Leung, and Shao 2002) use the Logistic missing mechanisms when the outcome is MNAR.”
• Efficient and Doubly Robust Imputation for Covariate-Dependent Missing Responses (2008, methodology): “Following the strategy of Qin, Leung, and Shao (2002), we consider an empirical likelihood based on observed values δ1, . . . , δn and (yi,Xi) with δi = 1, i = 1, . . . , n.”
• An Instrumental Variable Approach for Identification and Estimation with Nonignorable Nonresponse (2014, methodology): “Although Greenlees, Reece, and Zieschang (1982), Qin, Leung, and Shao (2002), Chang and Kott (2008), and Kott and Chang (2010) proposed some estimation methods, their results rely on the assumption that the observed likelihood is identifiable.”