Of the 28 studies, 3 used more than one sampling strategy. Purposeful Sampling in Implementation Research Characteristics of Implementation Research In implementation research, quantitative and qualitative methods often play important roles, either simultaneously or sequentially, for the purpose of answering the same question through convergence of results from different sources, answering related questions in a complementary fashion, using one set of methods to expand or explain the results obtained from use of the other set of methods, using one set of methods to develop questionnaires or conceptual models that inform the use of the other set, and using one set of methods to identify the sample for analysis using the other set of methods Palinkas et al.
Second, there are a not insignificant number in the qualitative methods field who resist or refuse systematic sampling of any kind and reject the limiting nature of such realist, systematic, or positivist approaches.
The single typical case study involved a simultaneous design where the qualitative study was embedded in a larger quantitative study for the purpose of complementarity Hoagwood et al.
Six studies used some form of maximum variation sampling to ensure representativeness and diversity of organizations and individual practitioners. Two of the six studies used maximum variation sampling in a sequential design Aarons et al. For example, participants in Homogenous Sampling would be similar in terms of ages, cultures, jobs or life experiences.
The remaining 20 studies provided no description of the sampling strategy used to identify participants for qualitative data collection and analysis; however, a rationale could be inferred based on a description of who were recruited and selected for participation.
Expert sampling Maximum variation sampling Maximum variation sampling, also known as heterogeneous sampling, is a purposive sampling technique used to capture a wide range of perspectives relating to the thing that you are interested in studying; that is, maximum variation sampling is a search for variation in perspectives, ranging from those conditions that are view to be typical through to those that are more extreme in nature.
In such cases, the entire population is often chosen because the size of the population that has the particular set of characteristics that you are interest in is very small. In this instance, the best sampling method to use is Total Population Sampling. This variety will, in turn, give you a better cross-section of information.
Qualitative research usually involves a number of different phases, with each phase building progressively onwards from the original.
However, such logical generalisations should be made carefully. The idea is to focus on this precise similarity and how it relates to the topic being researched. If that group is having problems, then we can be sure all the groups are having problems?
Table 2 below provides a description of the use of different purposeful sampling strategies in mixed methods implementation studies. TPS is a technique where the entire population that meet your criteria e. Total population sampling Total population sampling is a type of purposive sampling technique where you choose to examine the entire population i.
For example, if you are researching workplace packages that include dental benefits, then, logically, you would not include people who are unemployed or who have not been offered a benefits package by their place of work; they would be unable to relate anything relevant to your study.
The idea that a purposive sample has been created based on the judgement of the researcher is not a good defence when it comes to alleviating possible researcher biases, especially when compared with probability sampling techniques that are designed to reduce such biases.
These units may exhibit a wide range of attributes, behaviours, experiences, incidents, qualities, situations, and so forth. This can often help the researcher to identify common themes that are evident across the sample.
Advantages of purposive sampling There are a wide range of qualitative research designs that researchers can draw on.
This being the case, purposive sampling is useful to a researcher because they can use the variety of methods available to build and increase their research data. Achieving the goals of such qualitative research designs requires different types of sampling strategy and sampling technique.
These extreme or deviant cases are useful because they often provide significant insight into a particular phenomenon, which can act as lessons or cases of best practice that guide future research and practice.
To know if a case is decisive, think about the following statements: Researchers would be looking for variations in these cases to explain why their recoveries were atypical. In such instances, different types of sampling technique may be required at each phase.Explore the research methods terrain, read definitions of key terminology, and discover content relevant to your research methods journey.
Purposive sampling (also known as judgment, selective or subjective sampling) is a sampling technique in which researcher relies on his or her own judgment when choosing members of population to participate in the study.
One of the major benefits of purposive sampling is the wide range of sampling techniques that can be used across such qualitative research designs; purposive sampling techniques that range from homogeneous sampling through to critical case sampling, expert sampling, and more.
Sampling strategies for quantitative methods used in mixed methods designs in implementation research are generally well-established and based on probability theory.
In contrast, sampling strategies for qualitative methods in implementation studies are less explicit and often less evident.Download