Using a multiple imputation technique to merge data sets

Jeffrey Brown

Applied Economics Letters, 2002, vol. 9, issue 5, 311-314

Abstract: Surprisingly, despite the fact that the information needed to address a research question is often spread across separate surveys, there is not a well established method for merging data sets prior to analysis. This letter presents a relatively straightforward method for merging information from separate surveys of representative samples drawn from the same population. It uses a multiple imputation technique that was originally developed to correct for missing values on items from survey data. The advantage of the process is that it accounts for the variance related to merging separate data sets, as well as the sample variance present in any sample survey. This provides more accurate estimates of the precision of the coefficients of interest than ad hoc alternatives.

Date: 2002
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://www.informaworld.com/openurl?genre=article& ... 40C6AD35DC6213A474B5 (text/html)
Access to full text is restricted to subscribers.

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:taf:apeclt:v:9:y:2002:i:5:p:311-314

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/RAEL20

DOI: 10.1080/13504850110069980

Access Statistics for this article

Applied Economics Letters is currently edited by Anita Phillips

More articles in Applied Economics Letters from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().