Tuesday 16th July
Wednesday 17th July
Thursday 18th July
Friday 19th July
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Surveying immigrants in the absence of a sample frame 2 |
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| Convenor | Dr Yana Leontiyeva (Institute of Sociology, Academy of Sciences of the Czech Republic) |
| Coordinator 1 | Dr Agata Gorny (Centre of Migration Research, University of Warsaw) |
| Coordinator 2 | Ms Joanna Napierala (Centre of Migration Research, University of Warsaw) |
The aim of the proposed session is to attract contributions that address the methodological challenges posed by surveying respondents with immigrant-backgrounds, especially when an appropriate sample frame is not available. Conceptualising the sampling immigrants as a hard-to-reach population is relevant for (a) large national surveys that often underrepresent immigrants and (b) specific immigrant oriented surveys that often fail to produce data suitable for sophisticated statistical analysis.
The session welcomes contributions that address the following topics:
1) Use of innovative sampling methods like respondent-driven sampling, time-space sampling, quota sampling, random route sampling with focused enumeration, onomastic method in migration research.
2) Evaluations of survey data quality for immigrants in representative national and international surveys.
3) Presentation of particular immigrant surveys with a special focus on sampling techniques.
The repeated call for sound data in the area of migration has triggered several targeted surveys among specific immigrant groups in the past decade (e.g. Ersanilli/ Koopmans 2011, Latcheva et al. 2006, Crul et al. 2012, Morales/ Giugni 2011). Accompanying these data collection efforts research on collecting information on immigrants through surveys has advanced as well (e.g. Font/ Mendez forthcoming, Thomas 2008, Kraler/ Reichel 2010). Studies started looking into the main problems associated with surveying immigrants, mostly issues related to varying coverage and response rates of immigrant groups.
This paper evaluates a recent international sample survey, the Immigrant Citizens Survey, which aimed at surveying immigrants from outside the EU in 15 cities in seven EU countries (Huddleston/ Tjaden 2012). In five countries, Belgium, France, Hungary, Italy and Portugal, no sample frame was available for the target population. Consequently, alternative ways to obtain a representative sample had to be found. In three countries (HU, IT, PT), the so-called 'centers of aggregation sampling technique' (Baio et al. 2011) was employed, in France random dialling and in Belgium random routes including focused enumeration of the nearest neighbour technique were chosen as sampling strategies.
The paper assesses the main methodological challenges of carrying out a survey among a group of immigrants for whom no sampling frame exists. Furthermore, the samples of the survey in these five countries will be compared to results of official statistics in order to assess the accuracy of the samples obtained through the different sampling methods employed.
Migration research is an emerging field in the Czech Republic and the data collection poses many methodological challenges. Most of the problems connected with drawing a representative sample of immigrants in the Czech context originate from a lacking sample frame. There is no register of immigrants available for scientific research. However aggregated statistical data on registered immigrants are published regularly by the Czech Statistical Office. Probably, this is the reason why most of the Czech quantitative surveys of immigrants conducted between 2000 and 2013 applied quota sampling technique using known characteristics like sex, age, nationality and region. The aim of this presentation is to review four major Czech quota sample surveys of immigrants and to compare them in terms of methodology and basic results. The authors will try to investigate if the mentioned surveys produce stable results when it comes to the characteristics not controlled by the sample design and to draw some conclusions about the usefulness of quota sampling technique in the Czech context.
Mouw and Verdery (2012) show that it is possible to increase the efficiency of sampling from a hidden population by collecting network information as part of the survey. They propose a new method, "Network Sampling with Memory" (NSM) that information on network members from the survey instrument to uncover the sampling frame for the target population. NSM uses two sampling modes: a "Search" mode that uses the network data to explore under-sampled portions of the network, and a "List" mode that uses the network-based list of population members to sample randomly. In this paper, we present a practical application of NSM that reduces the cost of data collection by collecting contact information on up to three referrals from the current respondent, which eliminates the need to re-contact prior respondents to ask for referrals for new interviews. We test this modified method using simulated sampling on 215 school and university social networks and compare it to our previous results as well as the results that would be obtained using simple random sampling. In addition to the simulated tests, we test the accuracy and coverage of NSM in the field by conducting a network based household sample from a high-migration sending community in Mexico. By comparing the results of NSM to a household census of the community, we assess the efficiency of the method. Finally, as part of our field-test evaluation we provide a step-by-step description of carrying out an NSM-based survey in practice.
There is extensive interest in understanding more about immigrant populations in European countries, and about the integration of new immigrants more specifically. However, in countries without comprehensive register data, straightforward sampling frames are not typically available. Alongside ad hoc or opportunistic methods, there has been recent interest in extending Respondent Driven Sampling (RDS) from applications largely in the field of HIV and of drug-injecting populations, to surveying migrant groups. However, RDS depends on the population of interest being internally networked and, typically, geographically relatively concentrated, characteristics that new immigrant populations do not necessarily share.
This paper outlines the approach to sampling new immigrants for the UK arm of a four-country cross-national study of the socio-cultural integration of new immigrants. It describes the attempt to implement RDS alongside other methods, for two groups of recent immigrants, one from a group with an existing, longstanding migration history in the UK, Pakistanis, and one from a group that does not have that same history of long-term flows to the UK, Poles, but which constitutes one of the largest immigrant flows since 2004 and the A8 accession. The paper outlines the limitations of RDS in this context and the possible reasons, comparing the experience both between the two groups and with other recent studies that have attempted to implement RDS for immigrant populations. It concludes with some reflections on alternative approaches to sampling recent immigrants, and their costs and benefits.