Sampling for ehes
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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.

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Sampling for EHES

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Sampling for ehes

Sampling for EHES

EHES Training

Material


Ideal target population

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

Main sampling frame

  • The main sampling frame is the list ofpeople/addresses to take a sample from.

  • An ideal list is:

    • Updatedregularly

    • Includeseveryone in the target population

    • Containscontactinformation

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


Sampling designs

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)

An example country with random sampling

Clustering participants reduces costs


What is a multi stage sample

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 sample1

What is a multi-stage sample?

Stage 2

  • Within each selected PSU, people from the population registerare selected randomly

An example country


What is a multi stage sample2

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 sample3

What is a multi-stage sample?

Stage 3

  • Within each selected household we select all household members

An example country


What is a multi stage sample4

What is a multi-stage sample?

Stage 3

  • Within each selected household we select 1person

An example country


What is random selection

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

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

Stratification

  • Grouping similar PSUs or individuals during the sampling stage is called stratification

  • Stratification generally improvesthe accuracy of the estimates

2 PSU selected in each PSU (shown as white)

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


Biased samples

Population

Sample

Sample

Biased 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)

Population

Representative sample

Biased sample


Sample size

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

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 clusters

Very 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

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

Acknowledgements

  • Slides

    • Susie Jentoft and Johan Heldal


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