Loading...
Please wait, while we are loading the content...
Similar Documents
Combining Non-probability and Probability Survey Samples Through Mass Imputation
| Content Provider | Semantic Scholar |
|---|---|
| Author | Kim, Jae Kwang Park, Seho Chen, Yilin Wu, Changbao |
| Copyright Year | 2019 |
| Abstract | This paper presents theoretical results on combining non-probability and probability survey samples through mass imputation, an approach originally proposed by Rivers (2007) as sample matching without rigorous theoretical justification. Under suitable regularity conditions, we establish the consistency of the mass imputation estimator and derive its asymptotic variance formula. Variance estimators are developed using either linearization or bootstrap. Finite sample performances of the mass imputation estimator are investigated through simulation studies and an application to analyzing a non-probability sample collected by the Pew Research Centre. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | https://arxiv.org/pdf/1812.10694v3.pdf |
| Alternate Webpage(s) | https://lib.dr.iastate.edu/cgi/viewcontent.cgi?article=1268&context=stat_las_pubs |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
