<abstract xmlns="http://www.w3.org/1999/xhtml"><p>Adaptive survey designs (ASDs) optimize design features, given 1) the interactions between the design features and characteristics of sampling units and 2) a set of constraints, such as a budget and a minimum number of respondents. Estimation of the interactions is subject to both random and systematic error. In this article, we propose and evaluate four viewpoints to assess robustness of ASDs to inaccuracy of design parameter estimates: the effect of both imprecision and bias on both ASD structure and ASD performance. We additionally propose three distance measures to compare the structure of ASDs. The methodology is illustrated using a simple simulation study and a more complex but realistic case study on the Dutch Travel Survey. The proposed methodology can be applied to other ASD optimization problems. In our simulation study and case study, the ASD was fairly robust to imprecision, but not to realistic dynamics in the design parameters. To deal with the sensitivity of ASDs to changing design parameters, we recommend to learn and update the design parameters.</p></abstract>

Adaptive survey designs (ASDs) optimize design features, given 1) the interactions between the design features and characteristics of sampling units and 2) a set of constraints, such as a budget and a minimum number of respondents. Estimation of the interactions is subject to both random and systematic error. In this article, we propose and evaluate four viewpoints to assess robustness of ASDs to inaccuracy of design parameter estimates: the effect of both imprecision and bias on both ASD structure and ASD performance. We additionally propose three distance measures to compare the structure of ASDs. The methodology is illustrated using a simple simulation study and a more complex but realistic case study on the Dutch Travel Survey. The proposed methodology can be applied to other ASD optimization problems. In our simulation study and case study, the ASD was fairly robust to imprecision, but not to realistic dynamics in the design parameters. To deal with the sensitivity of ASDs to changing design parameters, we recommend to learn and update the design parameters.

Robustness of Adaptive Survey Designs to Inaccuracy of Design Parameters

Statistics Netherlands, Department of Process Development and Methodology

Journal of Official Statistics

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

{"article-title":"Robustness of Adaptive Survey Designs to Inaccuracy of Design Parameters"}

Adaptive survey designs (ASDs) optimize design features, given 1) the interactions between the design features and characteristics of sampling units and 2) a...

Robustness of Adaptive Survey Designs to Inaccuracy of Design Parameters

Publié en ligne: 09 sept. 2017

Pages: 687 - 708

Reçu: 01 mars 2016

Accepté: 01 juin 2017

DOI: https://doi.org/10.1515/jos-2017-0032

Mots clés
Mixed-mode survey, mode effect, optimization problem, sensitivity analysis, Travel Survey

© 2017 Joep Burger et al., published by De Gruyter Open

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

Robustness of Adaptive Survey Designs to Inaccuracy of Design Parameters

Publié en ligne: 09 sept. 2017

Pages: 687 - 708

Reçu: 01 mars 2016

Accepté: 01 juin 2017

DOI: https://doi.org/10.1515/jos-2017-0032

Mots clésMixed-mode survey, mode effect, optimization problem, sensitivity analysis, Travel Survey

© 2017 Joep Burger et al., published by De Gruyter Open

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

Mots clés
Mixed-mode survey, mode effect, optimization problem, sensitivity analysis, Travel Survey