Sampling methods in epidemiological studies

Abstract

Sampling allows researchers to obtain information about a population through data obtained from a subset of the population, with a saving in terms of costs and workload compared to a study based on the entire population. Sampling allows the collecting of high quality information, provided that the sample size is large enough to detect a true association between exposure and outcome. There are two types of sampling methods: probability and non-probability sampling. In probability sampling the subset of the population is extracted randomly from all eligible individuals; this method, as all subjects have a chance of being chosen, allows researchers to generalize the findings of their study. In non-probability sampling, some individuals have no chance of being selected, because researchers do not extract the sample from all eligible subjects of a population; the sample is probably non-representative, the effect of sampling error cannot be estimated, so that the study produces non-generalizable results. Examples of probability sampling methods are: simple random sampling, systematic sampling, stratified sampling, and clustered sampling. Examples of non-probability sampling methods are: convenience sampling, judgement sampling. (Epidemiology_statistics)