|
Activity Number:
|
169
- SPEED:Improving Survey Data Quality with Multiple Data Sources, Administrative Data, and Nonresponse Bias Control
|
|
Type:
|
Contributed
|
|
Date/Time:
|
Monday, July 29, 2019 : 10:30 AM to 12:20 PM
|
|
Sponsor:
|
Survey Research Methods Section
|
|
Abstract #306974
|
|
|
Title:
|
Variance Estimation for Nearest Neighbor Imputed Data
|
|
Author(s):
|
Xiaofei Zhang* and Wayne Fuller
|
|
Companies:
|
Iowa State Univ and Iowa State University
|
|
Keywords:
|
Imputation;
nearest neighbor;
variance estimation
|
|
Abstract:
|
Imputation is a procedure used to complete records for a subsample of a large sample, where a part of the large sample has complete records. An example is the National Resources Inventory, a longitudinal survey in which some units are observed every year and some units are observed periodically. Data for partially observed units are imputed using the units observed every year. We consider nearest neighbor imputation (NNI) and give some theoretical properties for the NNI estimator of the estimated mean. We give a variance estimator for the mean constructed with an imputed dataset with application to the National Resources Inventory.
|
Authors who are presenting talks have a * after their name.
