Sampling for EHES

EHES Training Material

Ideal target population• The core target population for EHES is all adults

aged 25 to 64 who reside in the country• The age range can be extended by the individual

countries• Institutionalized should be included• Temporary visitors are not included

Main sampling frame• The main sampling frame is the list of

people/addresses to take a sample from.• An ideal list is:

• Updated regularly• Includes everyone in the target population • Contains contact information

• In reality, add-on lists may be neccesary (especially for those in institutions)

Sampling designs• A sample is taken to represent the population as

a whole as we do not have the resources to survey everybody

• We recommend (for most counrties) a multi-stage design to reduce costs/resources through clustering participants into manageable areas known as Primary Sampling Units (PSUs)

Clustering participants reduces costsAn example country with random sampling

What is a multi-stage sample?

Stage 1• The country is divided into Primary Sampling Units

(PSUs)• A number of these are selected randomly

An example country

What is a multi-stage sample?

Stage 2• Within each selected PSU, people from the

population register are selected randomly

An example country

What is a multi-stage sample?

Stage 2• Within each selected PSU, households from a

household list are selected randomly

An example country

What is a multi-stage sample?

Stage 3• Within each selected household we select all

household members

An example country

Stage 3• Within each selected household we select 1

person

What is a multi-stage sample?

An example country

What is random selection?

• Selecting a person randomly means that they are selected entirely by chance

• We can calculate how likely someone is to be selected. We can not 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 (believe it or not)

• Replacing someone who does not want to/can not participate with somebody else means we no longer have a random sample and can not estimate health figures accurately from the data

Stratification• Grouping similar PSUs or individuals during the

sampling stage is called stratification• Stratification generally improves the accuracy of

the estimates

An example country with stratification of PSUs (shown by separate colours)

2 PSU selected in each PSU (shown as white)

Sample

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)

Biased sample

Sample

Population Population

Representative sample Biased sample

Sample size• A minimum sample size of 4000 is required in

countries implementing a multi-stage design for EHES• This is based on the accuracy required with response

rates of 70%• Based on a minimum of 500 in each of the 8 sex/age

groups groups (25-34, 35-44, 45-54, 55-64 years) • A one-stage designs allows a reduction in sample size• Sub-national estimates will most probably require a

larger sample size

Sample allocation• How to allocate the sample among the Primary

Sampling Units is a balance between resources and accuracy

• We recommend using the EHES program in R and/or a specialist survey statistician

No clustersVery good accuracy of estimates

High cost

Many small clusters

Medium accuracy of estimates

Medium cost

Few large clusters

Low accuracy of estimates

Low cost

General sampling tips• Sampling using multi-stage designs can be

complicated, however, can reduce overall costs while maintaining control over the accuracy of estimates

• An add-on package for the statistical software ”R” has been developed as a tool for sampling in EHES and is freely available

Acknowledgements• Slides

• Susie Jentoft and Johan Heldal