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- Articles and reports: 12-001-X202600100007Description: National statistical institutes operate sample coordination systems to spread the response burden in business surveys. Despite the applied sample coordination and monitoring the response burden, some businesses might still be heavily sampled within a short period. This may lead to a peaking response burden for individual businesses, which could affect response rates and response quality. This paper proposes a new sample coordination method based on Adapted Spatially Correlated Poisson (ASCP) sampling that focuses on businesses with a high response burden. The effects on the response burden will be evaluated in two simulation studies and compared with a stratified approach, a pragmatic method in which sampling fractions are manually adjusted and with the baseline method of ignoring the response burden. For the simulations, real-world scenarios and data from Statistics Netherlands are used. The first simulation study considers a practical situation in which a given sample is adjusted with the aim to avoid the occurrence of businesses with a peaking response burden. The second simulation study analyzes the longer-term effects of the different sample coordination methods and focuses both on the reduction and spread of the response burden. The advantages and disadvantages of the different methods will be explained and discussed in detail, and recommendations for applying these methods at national statistical institutes and other survey agencies will be given.Release date: 2026-06-29
- Articles and reports: 12-001-X202300200010Description: Sample coordination methods aim to increase (in positive coordination) or decrease (in negative coordination) the size of the overlap between samples. The samples considered can be from different occasions of a repeated survey and/or from different surveys covering a common population. Negative coordination is used to control the response burden in a given period, because some units do not respond to survey questionnaires if they are selected in many samples. Usually, methods for sample coordination do not take into account any measure of the response burden that a unit has already expended in responding to previous surveys. We introduce such a measure into a new method by adapting a spatially balanced sampling scheme, based on a generalization of Poisson sampling, together with a negative coordination method. The goal is to create a double control of the burden for these units: once by using a measure of burden during the sampling process and once by using a negative coordination method. We evaluate the approach using Monte-Carlo simulation and investigate its use for controlling for selection “hot-spots” in business surveys in Statistics Netherlands.Release date: 2024-01-03
Articles and reports (2)
Articles and reports (2) ((2 results))
- Articles and reports: 12-001-X202600100007Description: National statistical institutes operate sample coordination systems to spread the response burden in business surveys. Despite the applied sample coordination and monitoring the response burden, some businesses might still be heavily sampled within a short period. This may lead to a peaking response burden for individual businesses, which could affect response rates and response quality. This paper proposes a new sample coordination method based on Adapted Spatially Correlated Poisson (ASCP) sampling that focuses on businesses with a high response burden. The effects on the response burden will be evaluated in two simulation studies and compared with a stratified approach, a pragmatic method in which sampling fractions are manually adjusted and with the baseline method of ignoring the response burden. For the simulations, real-world scenarios and data from Statistics Netherlands are used. The first simulation study considers a practical situation in which a given sample is adjusted with the aim to avoid the occurrence of businesses with a peaking response burden. The second simulation study analyzes the longer-term effects of the different sample coordination methods and focuses both on the reduction and spread of the response burden. The advantages and disadvantages of the different methods will be explained and discussed in detail, and recommendations for applying these methods at national statistical institutes and other survey agencies will be given.Release date: 2026-06-29
- Articles and reports: 12-001-X202300200010Description: Sample coordination methods aim to increase (in positive coordination) or decrease (in negative coordination) the size of the overlap between samples. The samples considered can be from different occasions of a repeated survey and/or from different surveys covering a common population. Negative coordination is used to control the response burden in a given period, because some units do not respond to survey questionnaires if they are selected in many samples. Usually, methods for sample coordination do not take into account any measure of the response burden that a unit has already expended in responding to previous surveys. We introduce such a measure into a new method by adapting a spatially balanced sampling scheme, based on a generalization of Poisson sampling, together with a negative coordination method. The goal is to create a double control of the burden for these units: once by using a measure of burden during the sampling process and once by using a negative coordination method. We evaluate the approach using Monte-Carlo simulation and investigate its use for controlling for selection “hot-spots” in business surveys in Statistics Netherlands.Release date: 2024-01-03