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Replication data for: Beyond Reducing Nonresponse Bias: Modeling Item Nonresponse in Survey Research
hdl:1902.1/10381
Version: 1 – Released: Wed Nov 28 00:00:00 EST 2007
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If you use these data, please add the following citation to your scholarly references. Why cite?
Original Publication
Results found in this publication can be replicated using these data.
Cranmer, Skyler and Lee Walker, (2008) "Beyond Reducing Nonresponse Bias: Modeling Item Nonresponse in Survey Research". Conflict Management and Peace Science.
Data Citation Details
Study Global IDhdl:1902.1/10381
AuthorsSkyler Cranmer (Harvard University); Lee Walker (University of South Carolina)
Production Date2008
DistributorSkyler Cranmer
Distributor Contactscranmer@iq.harvard.edu
Distribution Date2007
Deposit DateJuly 02, 2007
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Abstract and Scope
Abstract

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. 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.

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"Replication data for: Beyond Reducing Nonresponse Bias: Modeling Item Nonresponse in Survey Research", hdl:1902.1/10381