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SAMPLING IN
QUALITATIVE
RESEARCH
Understanding sampling
• Probability (random) sampling
vs.
• Purposeful sampling
Purposeful sampling
• information-rich cases that can help answer research
questions
Purposeful sampling strategies
• Extreme cases
(outliers)
• Maximum variation
• Homogeneous groups
• Typical/average case
...
Extreme cases / outliers
• Cases that have gone extremely well or extremely wrong
– i.e. excellence or extreme failure
• I...
Maximum variation sampling
• Pick a few cases from different conditions: eg:
• very poor, middle class, very rich
• very l...
Homogeneous groups
• Small group of similar cases to describe in depth
• Used to gain information about a particular subgr...
Typical/average case
• Identified with the help of key informants or previous
research
• What criteria do you use to defin...
Critical case sampling
• If it happens here, it will happen everywhere
• e.g. if conservative group adopts new technology,...
Snowball / chain sampling
• Ask participants: who should I talk to? Who knows a lot
about… Who does… ?
Criterion sampling
• Participants must meet certain criteria
• EG:
• age requirements
• weekly users of Facebook, Twitter,...
Theory based sampling
• A type of criterion sampling
• The criteria are derived from theory
• EG:
• early adopters (diffus...
Confirming & disconfirming cases
• Confirming cases support your analysis
• Disconfirming cases contradict your analysis, ...
Stratified purposeful sampling
• Sampling within samples
• EG:
• 3 kinds of typical case: below average, average, above av...
Opportunistic / emergent sampling
• On-the-spot decisions in the field
Purposeful random sampling
• Used to select a small number of cases to study from a
large pool of available cases that qua...
Sample size in qualitative research
• Sample to the point of redundancy
• For IRB purposes, specify a safely large number
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Sampling in qualitative research

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Sampling in qualitative research

  1. 1. SAMPLING IN QUALITATIVE RESEARCH
  2. 2. Understanding sampling • Probability (random) sampling vs. • Purposeful sampling
  3. 3. Purposeful sampling • information-rich cases that can help answer research questions
  4. 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. 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. 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. 7. Homogeneous groups • Small group 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. 8. Typical/average case • Identified with the help of key informants or previous research • What criteria do you use to define typical? • e.g. Typical science classroom/prof
  9. 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. 10. Snowball / chain sampling • Ask participants: who should I talk to? Who knows a lot about… Who does… ?
  11. 11. Criterion sampling • Participants must meet certain criteria • EG: • age requirements • weekly users of Facebook, Twitter, AND LinkedIn • teach mathematics at x level
  12. 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. 13. Confirming & disconfirming cases • 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. 14. Stratified purposeful sampling • Sampling within samples • EG: • 3 kinds of typical case: below average, average, above average
  15. 15. Opportunistic / emergent sampling • On-the-spot decisions in the field
  16. 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. 17. Sample size in qualitative research • Sample to the point of redundancy • For IRB purposes, specify a safely large number

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