The use of epidemiological tools in conflict-affected populations: open-access educational resources for policy-makers

Table of Contents

1. Welcome
2. Introduction: Epidemiology in crises
3. Ethical issues in data collection
4. Need for epidemiologic competence
5. Surveys - Introduction
6. Surveys - Description of sampling methods
7. Surveys - Sampling error, bias, accuracy, precision, & sample size
   1. Bias and sampling error
   2. Bias and sampling error 2
   3. Bias
   4. Measurement bias
   5. Sampling bias
   6. Sampling error
   7. Bias and sampling error - Quiz
   8. Confidence intervals
   9. Confidence intervals - Quiz
   10. Accuracy and precision - theory
   11. Sample size
8. Surveys - Resources required for surveys
9. Surveys - Critiquing survey reports
10. Surveillance - When to do surveillance
11. Surveillance - Methods
12. Surveillance - Common problems
13. Programme data
14. Rapid assessment
15. Mortality - Indicators and their measurement
16. Mortality - Data sources
17. Mortality - Interpretation and action
18. Nutrition - Introduction and background
19. Nutrition - Indicators and their measurement
20. Nutrition - Data sources
21. Nutrition - Interpretation and action
22. Health services
23. Vaccination programmes
24. Water supply, sanitation, and shelter
25. Violence
26. Presentation of results
27. Formulating conclusions and recommendations
28. Dissemination and action

Sample size

(go to Outline)

How do we ensure enough precision to make good programmatic decisions after the survey results are analyzed?

Click here for the answer.

Why do we calculate sample size instead of just collecting data on many people?

Click here for answers.

Remember, if you calculate the sample size for the entire survey sample, you will not have much precision in your analysis of subgroups within the survey sample. For example, of you are doing a survey of three refugee camps and calculate a sample size for the entire survey of 554 households, you will not have much precision when analyzing only the households in one camp. So you will not be able to make estimates for your health indicators or outcomes for only one camp or compare one camp to another.

If a survey has not calculated the sample size beforehand, it may have wasted resources gathering more data than necessary. In addition, because supervision and training are more difficult with more teams and survey workers, not calculating sample size can lead to a greater chance of having bias in the survey results.

We won't go into calculating sample size here. Suffice it to say, many computer programmes do this for you, and many statistics books explain the process.

Here are some websites with explanations of calculating sample sizes:

University of Pittsburgh

Harvard Universtity