EconPapers    
Economics at your fingertips  
 

Item Response Rates for Composite Variables

Eggleston Jonathan ()
Additional contact information
Eggleston Jonathan: U.S. Census Bureau, 4600 Silver Hill Road, Washington DC, 20233, U.S.A.

Journal of Official Statistics, 2019, vol. 35, issue 2, 387-408

Abstract: Item response rates frequently serve as indicators of data quality and potential nonresponse bias. However, key variables from surveys, such as total household income or net worth, are often composite variables constructed from several underlying components. Because such composite variables do not have clearly identifiable response rates, inference on the data quality of these key measures is more difficult. This article proposes three new methods for aggregating data on response rates across questions to create a measure of item response for composite variables. To compare the three methods and illustrate how they can be used (both individually and collectively) to investigate data quality, I analyze item response for net worth in the Survey of Income and Program Participation (SIPP) and the Survey of Consumer Finances (SCF). These new measures provide detailed information about net worth estimates that would be difficult to assess without an item response aggregation method. Overall, these new item response rate methods provide a new way of describing data quality for key measures in surveys and for analyzing changes in data quality over time.

Keywords: Response rates; nonresponse (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://doi.org/10.2478/jos-2019-0018 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:vrs:offsta:v:35:y:2019:i:2:p:387-408:n:5

DOI: 10.2478/jos-2019-0018

Access Statistics for this article

Journal of Official Statistics is currently edited by Annica Isaksson and Ingegerd Jansson

More articles in Journal of Official Statistics from Sciendo
Bibliographic data for series maintained by Peter Golla ().

 
Page updated 2025-03-20
Handle: RePEc:vrs:offsta:v:35:y:2019:i:2:p:387-408:n:5