Selection of participants What fieldwork personnel need to understand Selection of participants

Available at:http://urn.fi/URN:ISBN:978-952-302-700-8 Based on EHES Manual, Part A. Planning and preparation of the survey, 2nd edition (2016) Available at:http://urn.fi/URN:ISBN:978-952-302-700-8 These slides can be used freely, translated and adapted to national use (e.g. concerning national sampling frames and sample selection criteria).

Who could be invited? In principle, every person aged 25 to 64 years living in the country is eligible Temporary visitors are not included in the survey

How were people selected? Stage 1 The country was divided into examination areas (Primary Sampling Units) A number of these were selected randomly With probability proportional to their size An example country

How were people selected? Stage 2 Within each selected examination area we selected people from the population register also randomly everyone got the same chance of being selected, at least approximately An example country

How were people selected? Stage 2 Within each selected examination area we selected households (dwellings) from a local household (address) list also randomly every household/dwelling had the same chance of being selected, at least approximately An example country

How were people selected? Stage 3 Within each selected household we selected all household members An example country

How were people selected? Stage 3 Within each selected household we selected 1 person An example country

What is random selection? Selecting a person, household, dwelling or area randomly means that they are selected entirely by chance We can calculate how likely someone is to be selected. We cannot calculate if they actually will be selected – this is the random part.

Why random selection? To estimate the health of the population we need to know everyone’s chances of being selected/invited This is only possible with random selection Replacing someone who does not want to or cannot participate with someone else means we no longer have a random sample and cannot estimate health figures accurately from the data

Biased samples A sample is biased if it does not reflect the population and will tend to give wrong results Biased samples can result from: Samples that are not randomly taken from the population Low response rates among certain groups of the sample (eg. people who are not well) Population Biased sample Sample Population Sample Representative sample

Acknowledgements Slides prepared by: Susie Jentoft, Johan Heldal and Kari Kuulasmaa Experiences and feedback from the EHES network have been utilized in the preparation of these slides Funding: Preparation of the slides is part of the activities of the EHES Coordinating Centre which has received funding from the EC/DG SANTÉ in 2009-2012 through SANCO/2008/C2/02-SI2.538318 EHES and Grand Agreement number 2009-23-01, and in 2015-2017 through Grand Agreement number 664691/BRIDGE Health

Disclaimer The views expressed here are those of the authors and they do not represent the Commission’s official position.