<abstract xmlns="http://www.w3.org/1999/xhtml"><p>Nonresponse rates have been growing over time leading to concerns about survey data quality. Adaptive designs seek to allocate scarce resources by targeting specific subsets of sampled units for additional effort or a different recruitment protocol. In order to be effective in reducing nonresponse, the identified subsets of the sample need two key features: 1) their probabilities of response can be impacted by changing design features, and 2) once they have responded, this can have an impact on estimates after adjustment. The National Agricultural Statistics Service (NASS) is investigating the use of adaptive design techniques in the Crops Acreage, Production, and Stocks Survey (Crops APS). The Crops APS is a survey of establishments which vary in size and, hence, in their potential impact on estimates. In order to identify subgroups for targeted designs, we conducted a simulation study that used Census of Agriculture (COA) data as proxies for similar survey items. Different patterns of nonresponse were simulated to identify subgroups that may reduce estimated nonresponse bias when their response propensities are changed.</p></abstract>

Nonresponse rates have been growing over time leading to concerns about survey data quality. Adaptive designs seek to allocate scarce resources by targeting specific subsets of sampled units for additional effort or a different recruitment protocol. In order to be effective in reducing nonresponse, the identified subsets of the sample need two key features: 1) their probabilities of response can be impacted by changing design features, and 2) once they have responded, this can have an impact on estimates after adjustment. The National Agricultural Statistics Service (NASS) is investigating the use of adaptive design techniques in the Crops Acreage, Production, and Stocks Survey (Crops APS). The Crops APS is a survey of establishments which vary in size and, hence, in their potential impact on estimates. In order to identify subgroups for targeted designs, we conducted a simulation study that used Census of Agriculture (COA) data as proxies for similar survey items. Different patterns of nonresponse were simulated to identify subgroups that may reduce estimated nonresponse bias when their response propensities are changed.

The Impact of Targeted Data Collection on Nonresponse Bias in an Establishment Survey: A Simulation Study of Adaptive Survey Design

Journal of Official Statistics

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Nonresponse rates have been growing over time leading to concerns about survey data quality. Adaptive designs seek to allocate scarce resources by targeting...

The Impact of Targeted Data Collection on Nonresponse Bias in an Establishment Survey: A Simulation Study of Adaptive Survey Design

Publié en ligne: 09 sept. 2017

Pages: 857 - 871

Reçu: 01 avr. 2016

Accepté: 01 avr. 2017

DOI: https://doi.org/10.1515/jos-2017-0039

Mots clés
Adaptive survey design, nonresponse bias, establishment surveys

© 2017 Jaki McCarthy et al., published by De Gruyter Open

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

The Impact of Targeted Data Collection on Nonresponse Bias in an Establishment Survey: A Simulation Study of Adaptive Survey Design

Publié en ligne: 09 sept. 2017

Pages: 857 - 871

Reçu: 01 avr. 2016

Accepté: 01 avr. 2017

DOI: https://doi.org/10.1515/jos-2017-0039

Mots clésAdaptive survey design, nonresponse bias, establishment surveys

© 2017 Jaki McCarthy et al., published by De Gruyter Open

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Mots clés
Adaptive survey design, nonresponse bias, establishment surveys