Volume 38 - Article 21 | Pages 513–548
Design and implementation of a high-quality probability sample of immigrants and ethnic minorities: Lessons learnt
|Date received:||12 Oct 2017|
|Date published:||13 Feb 2018|
|Keywords:||boost sample, ethnic minorities, immigrants, two-stage sampling, UK Household Longitudinal Study (UKHLS), United Kingdom|
Background: Surveys of immigrants face challenges of coverage, representativeness, and response rates. Longitudinal studies of immigrants and ethnic minorities, which have potential to address pressing issues in demographic research, are rare or partial. In the absence of register data, the highest quality approach is argued to be probability sampling using household screening.
Objective: To describe the design and implementation of a nationally representative probability sample of immigrants and ethnic minorities in the United Kingdom.
Methods: We boosted a nationally representative sample by using small-area census data to identify areas that covered the majority of immigrant and target ethnic minority populations and oversampled addresses from those areas using varying sampling fractions. Households were screened for eligibility based on whether they included a target immigrant/ethnic minority member. If so, all adult members were interviewed.
Results: We anticipated the main challenges would be: fewer eligible households than predicted in sampled areas due to geographical mobility; refusal of those screened to provide information on household eligibility; nonparticipation of eligible households. All these issues were found to some degree. We describe how we addressed them and with what success.
Conclusions: A careful design and robust fieldwork practices can enable a two-stage probability sampling to achieve good coverage and a much more representative sample of immigrants and ethnic minorities than with more ad hoc methods. The potential research payoffs are substantial.
Contribution: We demonstrate the potential for careful two-stage sampling on the back of an existing study for creating a high-quality multi-purpose survey of immigrants.
Peter Lynn - University of Essex, United Kingdom
Alita Nandi - University of Essex, United Kingdom
Violetta Parutis - University of Essex, United Kingdom
Lucinda Platt - London School of Economics and Political Science, United Kingdom
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