On a Modular Approach to the Design of Integrated Social Surveys

Ioannidis Evangelos (), Merkouris Takis (), Zhang Li-Chun (), Karlberg Martin (), Petrakos Michalis (), Reis Fernando () and Stavropoulos Photis ()
Additional contact information
Ioannidis Evangelos: Athens University of Economics and Business, Patission str. 76, 10434 Athens, Greece.
Merkouris Takis: Athens University of Economics and Business, Patission str. 76, 10434 Athens, Greece.
Zhang Li-Chun: University of Southampton, Southampton, SO17 1BJ, United Kingdom and Statistics Norway.
Karlberg Martin: European Commission (Eurostat), L-2920 Luxembourg.
Petrakos Michalis: Agilis SA, Acadimias 96-100, 10677 Athens, Greece
Reis Fernando: European Commission (Eurostat), L-2920 Luxembourg.
Stavropoulos Photis: Agilis SA, Acadimias 96-100, 10677 Athens, Greece.

Journal of Official Statistics, 2016, vol. 32, issue 2, 259-286

Abstract: This article considers a modular approach to the design of integrated social surveys. The approach consists of grouping variables into ‘modules’, each of which is then allocated to one or more ‘instruments’. Each instrument is then administered to a random sample of population units, and each sample unit responds to all modules of the instrument. This approach offers a way of designing a system of integrated social surveys that balances the need to limit the cost and the need to obtain sufficient information. The allocation of the modules to instruments draws on the methodology of split questionnaire designs. The composition of the instruments, that is, how the modules are allocated to instruments, and the corresponding sample sizes are obtained as a solution to an optimisation problem. This optimisation involves minimisation of respondent burden and data collection cost, while respecting certain design constraints usually encountered in practice. These constraints may include, for example, the level of precision required and dependencies between the variables. We propose using a random search algorithm to find approximate optimal solutions to this problem. The algorithm is proved to fulfil conditions that ensure convergence to the global optimum and can also produce an efficient design for a split questionnaire.

Keywords: Efficient design; respondent burden; sample allocation; simulated annealing; split questionnaire (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://doi.org/10.1515/jos-2016-0013 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:vrs:offsta:v:32:y:2016:i:2:p:259-286:n:1

DOI: 10.1515/jos-2016-0013

Access Statistics for this article

Journal of Official Statistics is currently edited by Annica Isaksson and Ingegerd Jansson

More articles in Journal of Official Statistics from Sciendo
Bibliographic data for series maintained by Peter Golla ().