|
Activity Number:
|
40
- Survey Weighting, Imputation, and Estimation
|
|
Type:
|
Contributed
|
|
Date/Time:
|
Monday, August 3, 2020 : 10:00 AM to 2:00 PM
|
|
Sponsor:
|
Government Statistics Section
|
|
Abstract #312310
|
|
|
Title:
|
Multiple Imputation of Missing Income and Marital Status of the Research and Development Survey (RANDS)
|
|
Author(s):
|
Guangyu Zhang* and Yulei He and Bill Cai and Chris Moriarity and Hee-Choon Shin and Van Parsons and Katherine Irimata and Jennifer D Parker
|
|
Companies:
|
National Center for Health Statistics and National Center for Health Statistics and National Center for Health Statistics and National Center for Health Statistics and National Center for Health Statistics and National Center for Health Statistics and National Center for Health Statistics and NCHS
|
|
Keywords:
|
Research and Development Survey;
multiple imputation;
missing data
|
|
Abstract:
|
The Research and Development Survey (RANDS) is a web survey conducted by the National Center for Health Statistics (NCHS). It is conducted via external contractors using their probability-sampled panels of web users. The questionnaire of RANDS includes mostly identical questions fielded on the corresponding National Health Interview Survey (NHIS), which is a cross-sectional survey conducted by the National Center for Health Statistics since 1957. Missing data in RANDS are common. Two important variables, family income and marital status, have around 20% and 13% missingness. To address the missing data issue, we develop a multiple imputation model to impute missing data for RANDS 2015 and 2016, with family income and marital status as key outcomes. A simulation study is conducted to test the imputation model.
|
Authors who are presenting talks have a * after their name.
