Constarium
← Search

Data · dataset · 2007

Replication data for: Beyond Reducing Nonresponse Bias: Modeling Item Nonresponse in Survey Research

Listed in Harvard Dataverse

This paper discusses the limitations of whitening out nonresponse bias with multiple imputation and discusses the extent to which item nonresponse can be modeled as a response in and of itself.

Description

Specifically, I propose three techniques for modeling nonresponse at two different levels. I introduce a technique for modeling nonresponse in a particular variable of interest with a regression model using multiply imputed values of the nonresponses as a key explanatory variable.

I then introduce two techniques for modeling nonresponse in a series of variables or over the entirety of the dataset. Finally, I introduce a technique for weighting respondents by their rate of response. The methods described in this paper are implemented in the free software which accompanies this research.

Links

Where it is published

Catalogue records · 1
Provenance · 1 source records, 6 field assertions
SourceKeyLast seenRaw
Harvard Dataversedoi:10.7910/DVN/KC7YPY14 d agoJSON v1
FieldAssertionExtractorEvidence
created_datesource · Harvard Dataverseconnector:dataverse@1.0.0
descriptionsource · Harvard Dataverseconnector:dataverse@1.0.0/description
publication_datesource · Harvard Dataverseconnector:dataverse@1.0.0
titlesource · Harvard Dataverseconnector:dataverse@1.0.0/name
updated_datesource · Harvard Dataverseconnector:dataverse@1.0.0
version_labelsource · Harvard Dataverseconnector:dataverse@1.0.0