Example: Typical-case sampling You are researching the reactions of 9th grade students to a job placement program. For this reason, typical case sampling allows you to compare samples, not generalize samples to populations. Keep in mind that the goal of typical case sampling is to illustrate a phenomenon, not to make generalized statements about the experiences of all participants. Participants are generally chosen based on their likelihood of behaving like everyone else sharing the same characteristics or experiences. Typical case sampling is used when you want to highlight what is considered a normal or average instance of a phenomenon to those who are unfamiliar with it. Using homogeneous sampling, you select Latinx directors of mental health services agencies, interviewing them about the challenges of implementing evidence-based treatments for mental health problems. Example: Homogeneous samplingContinuing your research on mental health services programs in your state, you are now interested in illuminating the experiences of different ethnicities through group interviewing. Homogeneous sampling is often used for selecting focus group participants. The idea is to focus on this precise similarity, analyzing how it relates to your research topic. Units in a homogeneous sample share similar traits or specific characteristics-e.g., life experiences, jobs, or cultures. Homogeneous sampling, unlike maximum variation sampling, aims to reduce variation, simplifying the analysis and describing a particular subgroup in depth. In this way, you can document unique or diverse variations that have emerged in different locations. Using maximum variation sampling, you select programs in urban and rural areas in different parts of the state, in order to capture maximum variation in location. Example: Maximum variation samplingSuppose you are researching the challenges of mental health services programs in your state. This helps researchers to examine a subject from different angles, identifying important common patterns that are true across variations. To ensure maximum variation, researchers include both cases, organizations, or events that are considered typical or average and those that are more extreme in nature. Maximum variation sampling, also known as heterogeneous sampling, is used to capture the widest range of perspectives possible. See editing example Maximum variation sampling Maximum variation (or heterogeneous) sampling.Purposive sampling methods and examplesĭepending on your research objectives, there are several purposive sampling methods you can use: The more information you have, the higher the quality of your sample.
For this reason, purposive sampling works best when you have a lot of background information about your research topic. The main goal of purposive sampling is to identify the cases, individuals, or communities best suited to helping you answer your research question. Perhaps you would like to access a particular subset of the population that shares certain characteristics, or you are researching issues likely to have unique cases. Purposive sampling is best used when you want to focus in depth on relatively small samples. Frequently asked questions about purposive sampling.Advantages and disadvantages of purposive sampling.