Methodological Considerations in Using Complex Survey Data: An Applied Example With the Head Start Family and Child Experiences Survey

Debbie L. Hahs-Vaughn (), Christine M. McWayne, Rebecca J. Bulotsky-Shearer, Xiaoli Wen and Ann-Marie Faria
Additional contact information
Debbie L. Hahs-Vaughn: Department of Educational Research, University of Central Florida, Orlando, FL, USA
Christine M. McWayne: Tufts University, Boston, MA, USA
Rebecca J. Bulotsky-Shearer: University of Miami, Miami, FL, USA
Xiaoli Wen: National-Louis University, Chicago, IL, USA
Ann-Marie Faria: American Institute for Research, Washington, DC, USA

Evaluation Review, 2011, vol. 35, issue 3, pages 269-303

Abstract: Complex survey data are collected by means other than simple random samples. This creates two analytical issues: nonindependence and unequal selection probability. Failing to address these issues results in underestimated standard errors and biased parameter estimates. Using data from the nationally representative Head Start Family and Child Experiences Survey (FACES; 1997 and 2000 cohorts), three diverse multilevel models are presented that illustrate differences in results depending on addressing or ignoring the complex sampling issues. Limitations of using complex survey data are reported, along with recommendations for reporting complex sample results.

Keywords: complex samples; survey weights; sampling weights; survey research; multilevel modeling (search for similar items in EconPapers)
Date: 2011
References: Add references at CitEc
Citations Track citations by RSS feed

Downloads: (external link)
http://erx.sagepub.com/content/35/3/269.abstract (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: http://EconPapers.repec.org/RePEc:sae:evarev:v:35:y:2011:i:3:p:269-303

Access Statistics for this article

More articles in Evaluation Review
Series data maintained by SAGE Publications ().