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
Slide 3
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
Slide 4
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
Slide 5
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
Slide 6
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
Slide 7
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
Slide 8
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