P&B Chapter 21 Flashcards
(24 cards)
Also called volunteer sampling - used when researchers need potential participants to come forward and identify themselves
Convenience Sampling
What type of sampling? In-depth interviews with Latino and Caucasian clients with Type 2 diabetes about their dietary and self-management goal behaviors - sampled from a community/migrant health clinic in rural Washington state.
Convenience
Also called chain sampling; ask early informants to refer other study participants; tends to be more cost-efficient and practical; weakness is that it can restrict sample to a small social network of participants
Snowball sampling
Selecting cases that will most benefit the study (purposeful sampling)
Purposive sampling
What are the two general goals of purposive sampling?
- sampling to find examples that are representative or typical of a broader group on some dimension of interest
- sampling to set up the possibility of comparisons or replications across different types of cases on a dimension of interest
Most widely used method of purposive sampling; purposefully selecting persons (or settings) with a wide range of variation on dimensions of interest; might ensure people with diverse backgrounds are represented in the sample
Maximum variation sampling
Deliberately reduces variation and permits more focused inquiry; may use this approach if they wish to understand a particular group of people especially well; often used to select people for group interviews
Homogenous sampling
Selecting cases that illustrate or highlight what is typical, average, normal, or representative
Typical case sampling
Typical case sampling can be expanded by selecting a _____ ______ _____ of average, above average, and below average cases
Stratified purposive sample
Also called outlier sampling; provides opportunities for learning from the most unusual and extreme informants; most often a supplement to other sampling strategies because they can distort the understanding of a phenomenon if used normally
Extreme (deviant) case sampling
Similar to extreme case sampling but with less emphasis on the extremes; involves information-rich cases that manifest the phenomenon of interest intensely, but not as extreme or potentially distorting manifestations; selecting rich cases that offer strong examples of the phenomenon
Intensity sampling
Selecting cases based on a recommendation of an expert or key informant (most often used in ethnographies)
Reputational case sampling
Selecting important cases regarding the phenomenon of interest
critical case sampling
selecting cases that meet a predetermined criterion of importance
Criterion sampling
Identifying and gaining access to a single case representing a phenomenon that was previously inaccessible to research scrutiny
Revelatory case sampling
This approach is used to select or search for politically sensitive cases (or sites) for analysis
Sampling of politically important cases
Adding new cases to a sample based on changes in research circumstances as data are being collected, or in response to new leads and opportunities that may develop in the field
Opportunistic sampling
Tends to be used towards the end of data collection; involves testing ideas and assessing the viability of emergent findings and conceptualizations with new data
Sampling confirming and disconfirming cases
Additional cases that fit researchers’ conceptualizations and offer enhanced credibility, richness, and depth to the analysis and conclusions
confirming cases
examples that do not fit and serve to challenge researchers’ interpretations
disconfirming (negative) cases
strategy involving selection of “incidents, slices of life, time periods, or people on the basis of their potential manifestation or representation of important theoretical constructs”; complex sampling technique that requires researchers to be involved with multiple lines and directions as they go back and forth between data and categories in the emerging theory
theoretical sampling
Sampling to the point at which no new information is obtained and redundancy is achieved
data saturation
Number of participants needed to reach saturation depends on several factors (name the 4)
- scope of the research question (the broader the scope, the more participants likely needed)
- data quality (the better the participants and the more they share, the smaller the needed sample size)
- sensitivity of the phenomenon being studied
- skills and experiences of the researcher
Name the three models of generalizability
- Extrapolating from a sample to a population
- Analytic or conceptual generalization
- Case-to-case translation (transferability)