Sampling Frameworks
Definition: Sampling frameworks are techniques for determining who will be in a study. In order to make appropriate statistical inferences, representative samples are necessary. There are many types of sampling frameworks that can be used to best provide information about a population.
Random Sampling
Random sampling is a technique in which every member of the population has an equal and known chance of being selected to participate in the study and each person is randomly chosen to participate. This requires a complete enumeration of the population. In order for everyone to have an equal chance of being selected, there must be some complete pool from which to draw the sample.
Systematic Random Sampling
Systematic random sampling is a method by which every Nth person (e.g. every 3rd, 10th, or 50th person) is selected to participate as a means of randomly selecting participants. For instance, every 10th person could be selected from a phonebook, health insurance enrollment list or school enrollment list and contacted to participate in the study. Keep in mind that as with random sampling, a pool must exist from which to select your sample. If you use the phone book, a sample representing everyone who is in the phone book, not everyone who is in the population, will be obtained.
Convenience Sampling
Convenience sampling is a technique where participants are selected out of convenience instead of randomly. For instance, if someone is interested in how church-goers feel about a certain issue, they may stand outside a church to wait for exiting people and ask them to participate in the study. This technique is often used in exploratory research, in which more expensive sampling techniques are not practical. This technique is less expensive, easier to accomplish and less representative of the population. It is used for developing hypotheses, but not for testing hypotheses.
