Modeling Nonresponse in Establishment Surveys: Using an Ensemble Tree Model to Create Nonresponse Propensity Scores and Detect Potential Bias in an Agricultural Survey


Earp, Morgan ; Mitchell, Melissa ; McCarthy, Jaki ; Kreuter, Frauke


DOI: https://doi.org/10.2478/jos-2014-0044
URL: https://www.degruyter.com/downloadpdf/j/jos.2014.3...
Document Type: Article
Year of publication: 2014
The title of a journal, publication series: Journal of Official Statistics : JOS
Volume: 30
Issue number: 4
Page range: 701-719
Place of publication: Stockholm
Publishing house: Statistics Sweden
ISSN: 0282-423X
Publication language: English
Institution: Außerfakultäre Einrichtungen > Mannheim Centre for European Social Research - Research Department A
Subject: 300 Social sciences, sociology, anthropology
Abstract: Increasing nonresponse rates in federal surveys and potentially biased survey estimates are a growing concern, especially with regard to establishment surveys. Unlike household surveys, not all establishments contribute equally to survey estimates. With regard to agricultural surveys, if an extremely large farm fails to complete a survey, the United States Department of Agriculture (USDA) could potentially underestimate average acres operated among other things. In order to identify likely nonrespondents prior to data collection, the USDA’s National Agricultural Statistics Service (NASS) began modeling nonresponse using Census of Agriculture data and prior Agricultural Resource Management Survey (ARMS) response history. Using an ensemble of classification trees, NASS has estimated nonresponse propensities for ARMS that can be used to predict nonresponse and are correlated with key ARMS estimates.

Dieser Eintrag ist Teil der Universitätsbibliographie.




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Earp, Morgan ; Mitchell, Melissa ; McCarthy, Jaki ; Kreuter, Frauke ORCID: 0000-0002-7339-2645 (2014) Modeling Nonresponse in Establishment Surveys: Using an Ensemble Tree Model to Create Nonresponse Propensity Scores and Detect Potential Bias in an Agricultural Survey. Journal of Official Statistics : JOS Stockholm 30 4 701-719 [Article]


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ORCID: Earp, Morgan ; Mitchell, Melissa ; McCarthy, Jaki ; Kreuter, Frauke ORCID: 0000-0002-7339-2645

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