Replication Data for: Countering Non-Ignorable Nonresponse in Survey Models with Randomized Response Instruments and Doubly Robust Estimation (doi:10.7910/DVN/L2NVRD)

View:

Part 1: Document Description
Part 2: Study Description
Part 5: Other Study-Related Materials
Entire Codebook

Document Description

Citation

Title:

Replication Data for: Countering Non-Ignorable Nonresponse in Survey Models with Randomized Response Instruments and Doubly Robust Estimation

Identification Number:

doi:10.7910/DVN/L2NVRD

Distributor:

Harvard Dataverse

Date of Distribution:

2024-06-29

Version:

1

Bibliographic Citation:

Bailey, Michael, 2024, "Replication Data for: Countering Non-Ignorable Nonresponse in Survey Models with Randomized Response Instruments and Doubly Robust Estimation", https://doi.org/10.7910/DVN/L2NVRD, Harvard Dataverse, V1

Study Description

Citation

Title:

Replication Data for: Countering Non-Ignorable Nonresponse in Survey Models with Randomized Response Instruments and Doubly Robust Estimation

Identification Number:

doi:10.7910/DVN/L2NVRD

Authoring Entity:

Bailey, Michael (Georgetown University)

Producer:

<i>Political Analysis</i>

Distributor:

Harvard Dataverse

Access Authority:

Bailey, Michael

Depositor:

Bailey, Michael

Date of Deposit:

2024-04-15

Holdings Information:

https://doi.org/10.7910/DVN/L2NVRD

Study Scope

Keywords:

Social Sciences, Survey research

Abstract:

Conventional survey tools such as weighting do not address non-ignorable nonresponse that occurs when nonresponse depends on the variable being measured. This paper describes non-ignorable nonresponse weighting and imputation models using randomized response instruments, which are variables that affect response but not the outcome of interest \citep{SunEtal2018}. The paper uses a doubly robust estimator that is valid if one, but not necessarily both, of the weighting and imputation models is correct. When applied to a national 2019 survey, these tools produce estimates that suggest there was non-trivial non-ignorable nonresponse related to turnout, and, for subgroups, Trump approval and policy questions. For example, the conventional MAR-based weighted estimates of Trump support in the Midwest were 10 percentage points lower than the MNAR-based estimates. Data to replicate estimation described in "Countering Non-Ignorable Nonresponse in Survey Models with Randomized Response Instruments and Doubly Robust Estimation"

Methodology and Processing

Sources Statement

Data Access

Other Study Description Materials

Related Publications

Citation

Title:

Forthcoming, Political Analysis

Identification Number:

add DOI# here when available. If not available, please delete all text in this field before saving

Bibliographic Citation:

Forthcoming, Political Analysis

Other Study-Related Materials

Label:

README.txt

Notes:

text/plain

Other Study-Related Materials

Label:

Replication.zip

Notes:

application/zip