Responding driven sampling Principles of Sampling Session 1.

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Responding driven sampling Principles of Sampling Session 1

After this session, you should be able to Outline the purpose of sampling Understand key theoretical concepts in sampling Describe the concept of selection bias and random error in sampling 2WWW.HIVHUB.IR

Why do we sample? We sample when we desire to measure characteristics of a specified population (e.g., the proportion of the general population who have unsafe sex) but lack the time and resources to obtain information from all members of the population. Concentrating survey time and resources on a sample may also result in better quality data than if resources were spread over the whole population. 3WWW.HIVHUB.IR

Key definitions Sampling unit (element): Subject under observation on which information is collected – Example: adults<25 years, prisoners discharges Sampling fraction: Ratio between sample size and population size – Example: 100 out of 2000 (5%) Census: The variable(s) of interest is measured in all sampling units 4WWW.HIVHUB.IR

Key definitions Sampling frame List of all the sampling units from which sample is drawn – Lists: e.g. Adults< 25 years of age, households, health care units… Sampling scheme Method of selecting sampling units from sampling frame – Simple Random, convenience sample… 5WWW.HIVHUB.IR

Key definitions The target population is the population that is the ideal one for meeting a survey’s measurement objective. (For example, all commercial sex workers in a city.) The study (statsitical) population is the target population modified to take into account practical considerations (For example, all commercial sex workers in a city over the age of 15, excluding those who are home-based.) 6WWW.HIVHUB.IR

Target population-> Study Population-> Sample 7WWW.HIVHUB.IR Target Population: All homeless in country X Study Population: All homeless in capital shelters in the Sample: Homeless at particular shelter