Target population-> Study Population-> Sample 1WWW.HIVHUB.IR Target Population: All homeless in country X Study Population: All homeless in capital shelters.

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Presentation transcript:

Target population-> Study Population-> Sample 1WWW.HIVHUB.IR Target Population: All homeless in country X Study Population: All homeless in capital shelters in the Sample: Homeless at particular shelter

What do we want from our sample? Unbiased estimates of our indicators = Low Systematic Error Precise estimates of our indicators = Low Random Error 2WWW.HIVHUB.IR

Selection biases Selection biases, that pose a threat to external validity 3WWW.HIVHUB.IR Target Population Study Population Non- participants Participants Remaining part Response Non- Response

How to avoid selection biases Avoiding selection bias requires a random/probability sample. Monitoring the sampling process from the beginning to the end of the survey. 4WWW.HIVHUB.IR

Precise estimates Parameter: the value of our variable in the whole population Statistics: the value of a variable in the sample Standard error: is a measure which shows how much our statistics is close to the parameter 5WWW.HIVHUB.IR

How to improve the precision Standard error (or precision) depends upon: – Size of the sample ( Total / Efficient sample size) – Distribution of character of interest in the population 6WWW.HIVHUB.IR

General Conclusion In HIV surveillance surreys, we have to estimate relevant indicators in the whole population, and/or in the most at risk groups. Since, census is impossible, we have to measure these indicators in a sample and extrapolate the findings to the whole target population To increase the accuracy, we have to have an unbiased sample with reasonable sample size 7WWW.HIVHUB.IR