Uploaded byDr. V Vorvoreanu
Sampling in qualitative research
This document discusses various sampling strategies used in qualitative research including: 1) Purposeful sampling is used to select information-rich cases to answer research questions, such as extreme or typical cases. 2) Specific purposeful sampling strategies are described like maximum variation which selects cases from different conditions, and homogeneous groups which provides an in-depth look at a subgroup. 3) Other strategies discussed include snowball sampling which asks participants who else to interview, criterion sampling which uses predetermined criteria, and opportunistic sampling which makes on-the-spot decisions in the field.
In this document
Powered by AI
Introduction to the concept of sampling within qualitative research.
Discussion on two main sampling techniques: probability (random) and purposeful sampling.
Focus on purposeful sampling, targeting information-rich cases to answer specific research questions.
Overview of various purposeful sampling strategies such as extreme cases, maximum variation, and others.
Explains extreme cases/outliers that highlight successful or failed instances to inform other cases.
Focuses on selecting diverse cases to identify shared patterns across different demographics or conditions.
Describes sampling within small, similar groups to gain in-depth insights into specific subgroups.
Identifying typical cases through key informants to establish criteria for what 'typical' means.
A method indicating that findings from one case can apply broadly to other scenarios.
Utilizes participant recommendations to connect with more knowledgeable individuals about the study.
Involves selecting participants based on specific predefined criteria such as age or social media usage.
Criteria for participant selection derived from theoretical foundations related to the research.
Identifying cases that either support or contradict findings to deepen research analysis and exploration.
Sampling strategy involving subdivisions within samples to identify variations among different cases.
Allows researchers to make spontaneous sampling decisions based on emerging situations in the field.
Selects cases randomly from a larger pool that meet the study's criteria for targeted research.
Emphasizes determining a sample size that achieves data saturation for qualitative research validity.
More Related Content
Similar to Sampling in qualitative research
![Sampling1[1]](https://cdn.slidesharecdn.com/ss_thumbnails/sampling11-120509162836-phpapp02-thumbnail.jpg?width=640&height=640&fit=bounds)
![6Sampling[1].ppt 6Sampling[1].ppt 6Sampling[1].ppt](https://cdn.slidesharecdn.com/ss_thumbnails/6sampling1-250127151710-704b8b7a-thumbnail.jpg?width=640&height=640&fit=bounds)
Sampling in qualitative research
- 1.
- 2. Understanding sampling • Probability(random) sampling vs. • Purposeful sampling
- 3. Purposeful sampling • information-richcases that can help answer research questions
- 4. Purposeful sampling strategies •Extreme cases (outliers) • Maximum variation • Homogeneous groups • Typical/average case • Critical case • Snowball • Criterion • Theory-based • Confirming & disconfirming cases • Stratified purposeful • Opportunistic/emergen t • Purposeful random
- 5. Extreme cases /outliers • Cases that have gone extremely well or extremely wrong – i.e. excellence or extreme failure • Illuminative of other, less extreme instances
- 6. Maximum variation sampling •Pick a few cases from different conditions: eg: • very poor, middle class, very rich • very large, medium, small (town, class, college) • Identify shared patterns across these variations
- 7. Homogeneous groups • Smallgroup of similar cases to describe in depth • Used to gain information about a particular subgroup (i.e. single dads) • Used in focus group research
- 8. Typical/average case • Identifiedwith the help of key informants or previous research • What criteria do you use to define typical? • e.g. Typical science classroom/prof
- 9. Critical case sampling •If it happens here, it will happen everywhere • e.g. if conservative group adopts new technology, every other group will
- 10. Snowball / chainsampling • Ask participants: who should I talk to? Who knows a lot about… Who does… ?
- 11. Criterion sampling • Participantsmust meet certain criteria • EG: • age requirements • weekly users of Facebook, Twitter, AND LinkedIn • teach mathematics at x level
- 12. Theory based sampling •A type of criterion sampling • The criteria are derived from theory • EG: • early adopters (diffusion of innovations) • high communication apprehension • spatial learners
- 13. Confirming & disconfirmingcases • Confirming cases support your analysis • Disconfirming cases contradict your analysis, prompt you to look for alternate explanations • Used later in the research process, after patterns have emerged • EG • non-traditional students who do learn better when using the Smart Pen • non-traditional students who perform worse when using the Smart Pen
- 14. Stratified purposeful sampling •Sampling within samples • EG: • 3 kinds of typical case: below average, average, above average
- 15. Opportunistic / emergentsampling • On-the-spot decisions in the field
- 16. Purposeful random sampling •Used to select a small number of cases to study from a large pool of available cases that qualify • EG: • typical case sampling: pick 5 out of 50 cases
- 17. Sample size inqualitative research • Sample to the point of redundancy • For IRB purposes, specify a safely large number