Indicators for monitoring and improving representativeness of response
Indicators for monitoring and improving representativeness of response
The increasing efforts and costs required to achieve survey response have led to a stronger focus on survey data collection monitoring by means of paradata and to the rise of adaptive and responsive survey designs. Indicators that support data collection monitoring, targeting and prioritizing in such designs are not yet available. Subgroup response rates come closest but do not account for subgroup size, are univariate and are not available at the variable level.
We present and investigate indicators that support data collection monitoring and effective decisions in adaptive and responsive survey designs. As they are natural extensions of R-indicators, they are termed partial R-indicators. We make a distinction between unconditional and conditional partial R-indicators. Conditional partial R-indicators provide a multivariate assessment of the impact of register data and paradata variables on representativeness of response.
We propose methods for estimating partial indicators and investigate their sampling properties in a simulation study.. The use of partial indicators for monitoring and targeting nonresponse is illustrated for both a a household and business survey. Guidelines for the use of the indicators are given.
auxiliary variable, business survey, nonresponse, response propensity
Southampton Statistical Sciences Research Institute, University of Southampton
Schouten, Barry
69cdfe11-7450-4728-ae34-51755985ab88
Shlomo, Natalie
e749febc-b7b9-4017-be48-96d59dd03215
Skinner, Chris
dec5ef40-49ef-492a-8a1d-eb8c6315b8ce
18 June 2010
Schouten, Barry
69cdfe11-7450-4728-ae34-51755985ab88
Shlomo, Natalie
e749febc-b7b9-4017-be48-96d59dd03215
Skinner, Chris
dec5ef40-49ef-492a-8a1d-eb8c6315b8ce
Schouten, Barry, Shlomo, Natalie and Skinner, Chris
(2010)
Indicators for monitoring and improving representativeness of response
Southampton Statistical Sciences Research Institute, University of Southampton
Record type:
Monograph
(Working Paper)
Abstract
The increasing efforts and costs required to achieve survey response have led to a stronger focus on survey data collection monitoring by means of paradata and to the rise of adaptive and responsive survey designs. Indicators that support data collection monitoring, targeting and prioritizing in such designs are not yet available. Subgroup response rates come closest but do not account for subgroup size, are univariate and are not available at the variable level.
We present and investigate indicators that support data collection monitoring and effective decisions in adaptive and responsive survey designs. As they are natural extensions of R-indicators, they are termed partial R-indicators. We make a distinction between unconditional and conditional partial R-indicators. Conditional partial R-indicators provide a multivariate assessment of the impact of register data and paradata variables on representativeness of response.
We propose methods for estimating partial indicators and investigate their sampling properties in a simulation study.. The use of partial indicators for monitoring and targeting nonresponse is illustrated for both a a household and business survey. Guidelines for the use of the indicators are given.
Text
s3ri-workingpaper-M10-03.pdf
- Other
More information
Published date: 18 June 2010
Keywords:
auxiliary variable, business survey, nonresponse, response propensity
Identifiers
Local EPrints ID: 158353
URI: http://eprints.soton.ac.uk/id/eprint/158353
PURE UUID: e9f058e4-7d59-45bf-8afa-3c3cb42f8539
Catalogue record
Date deposited: 23 Jun 2010 08:22
Last modified: 15 Mar 2024 12:58
Export record
Contributors
Author:
Barry Schouten
Author:
Natalie Shlomo
Author:
Chris Skinner
Download statistics
Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.
View more statistics