The document discusses various sampling techniques used in qualitative research. It begins by defining key sampling concepts like sampling frame, sample design, and sample size. It then outlines prerequisites to consider for sampling like research objectives, target population, and budget. The main types of sampling covered are probabilistic, non-probabilistic, and mixed. Specific non-probabilistic strategies discussed include purposive sampling, convenience sampling, and quota sampling. The document concludes by noting biases that can occur in sampling and emphasizing that non-probabilistic techniques are commonly used in qualitative research.

1. Sampling in qualitative research

2. Plan of presentation
 Sampling introduction
 Pre requisite of sampling
 Types of sampling
 Qualitative research introduction
 Sampling strategies
 Advantages and disadvantages
 Summary
 References

3. Sampling
 Sample: A subset of the population being studied from which data is
actually collected.
 Sampling frame: This is the actual list of sampling units from which
the sample, or some stage of the sample, is selected. It is simply a list
of the study population.

4. Contd.
 Sample design: This refers to a set of rules or procedures
that specify how a sample is to be selected.
 Sample size: The number of elements in the obtained
sample.
 Sampling : The processes by which the subset of the
population from which you will collect data are chosen

5. Pre requisites of sampling
 What are the research objectives?
 What is the target population?
 Who should be inclusion criteria
 Who should be exclusion criteria
 What is the budget?
 What is the reporting time period?
 How many qualified researchers are available to work on the
project?
 What sampling technique(s) should be employed?

6. Contd.
 How are the data to be analysed?
 What data collection methods should be employed?
 How long will the interview be?
 Sample size?
 Sampling frame?
 How should potential respondents/participants be recruited?

7. Types of sampling
 Probabilistic : A sampling method where the probability
of selection of population elements is known.
 Non-probabilistic :The process of selecting a sample
from a population without using (statistical) probability
theory.
 Mixed

8. What a qualitative researcher worries about

9. Qualitative research
 When the paramount objective is “understanding
 When variables cannot be quantified
 When variables are best understood in their natural settings
 When studying intimate details
of roles, processes, and groups

10. Sampling strategies
 Purposive or Judgemental Sampling
A. Sampling to Achieve Representativeness or Comparability
B. Sampling Special or Unique Cases
C. Sequential Sampling
D. Sampling Using Multiple Purposive Techniques
 Convenience Sampling
A. Captive Sample
B. Volunteer Sample

11. Others
 Stakeholder
 Paradigmatic
 Purposeful Random Sampling
 Stratified Purposeful Sampling
 Expert sampling
 Quota sampling

12. I- Sampling to achieve representativeness
or comparability
 These techniques are used when the researcher wants
to :
(a) select a purposive sample that represents a broader
group of cases as closely as possible or
(b) set up comparisons among different types of cases

13. a)Typical case sampling or modal instance
 Focuses on what is typical, normal, and/or average. This
strategy may be adopted when one needs to present a
qualitative profile of one or more typical cases.
 When using this strategy you must have a broad
consensus about what is “average.”
 Ex:typical voter

14. b)Extreme or deviant case sampling
 Looks at highly unusual manifestations of the
phenomenon of interest, such as outstanding
success/notable failures, top of the class/dropouts, exotic
events, crises.
 This strategy tries to select particular cases that would
glean the most information, given the research question

15. c)Intensity sampling
 Chooses information-rich cases that manifest the
phenomenon intensely, but not extremely, such as good
students/poor students, above average/below average.
 This type of sampling requires that you have prior
information on the variation of the phenomena.
 Ex:jeolousy reaction

16. d)Maximum variation sampling
 Selects a wide range of variation on dimensions of
interest. The purpose is to discover/uncover central
themes, core elements, and/or shared dimensions that cut
across a diverse sample while at the same time offering
the opportunity to document unique or diverse variations.
 Aka phenomenal variation sampling.

17. e)Homogenous sampling
 Brings together people of similar backgrounds and
experiences. It reduces variation, simplifies analysis, and
facilitates group interviewing.
 This strategy is used most often when conducting focus
groups.

18. f)Reputational case sampling
 Variant of snowball sampling
 Ease of identifying the first case.
 Example :traffic signal beggars.

19. II- Sampling special or unique cases
 Employed when the individual case itself, or a specific
group of cases, is a major focus of the investigation
(rather than an issue).

20. a)Revelatory case sampling
 It involves identifying and gaining entry to a single case
representing a phenomenon that had previously been
‘inaccessible to scientific investigation’’.
 Such cases are rare and difficult to study, yet yield very
valuable information about heretofore unstudied
phenomena.

21. b)Critical case sampling
 Looks at cases that will produce critical information. In
order to use this method, you must know what constitutes
a critical case.
 This method permits logical generalization and maximum
application of information to other cases because if it's
true of this one case, it's likely to be true of all other case.
 Ex: federal rules and lawyers

22. c)Sampling politically important cases
 Seeks cases that will increase the usefulness and relevance
of information gained based on the politics of the
moment.
 This strategy attracts attention to the study (or avoids
attracting undesired attention by purposefully eliminating
from the sample politically sensitive cases). This strategy
is a variation on critical case sampling.

23. d)Criterion sampling
 Selects all cases that meet some criterion.
 This strategy is typically applied when considering quality
assurance issues. In essence, you choose cases that are
information-rich and that might reveal a major system
weakness that could be improved.
 Ex:hospital stay.

24. III- Sequential sampling
 Uses the gradual selection principle of sampling when
(a) the goal of the research project is the generation of
theory (or broadly defined themes) or
(b) the sample evolves of its own accord as data are being
collected.

25. a)Theoretical or operational construct sampling
 Identifies manifestations of a theoretical construct of
interest so as to elaborate and examine the construct.
 This strategy is used in grounded theory studies.
 You would sample people/incidents, etc., based on
whether or not they manifest/represent an important
theoretical or operational construct.

26. b)Confirming or disconfirming cases
 Seeks cases that are both “expected” and the “exception” to what is
expected. In this way, this strategy deepens initial analysis, seeks
exceptions, and tests variation.
 In this strategy you find both confirming cases (those that add depth,
richness, credibility) as well as disconfirming cases (example that do
not fit and are the source of rival interpretations).
 This strategy is typically adopted after initial fieldwork has established
what a confirming case would be. Ex: academics &environment.

27. c)Opportunistic or emergent sampling
 Follows new leads during fieldwork, takes advantage of
the unexpected, and is flexible. This strategy takes
advantage of whatever unfolds as it is unfolding, and may
be used after fieldwork has begun and as a researcher
becomes open to sampling a group or person they may not
have initially planned to interview.

28. d)Snowball sampling
 This is an approach used for locating information-rich
cases.
 Used mostly to reach out to “hard to find population”
 Nominated ,chain- referral, link tracing, network sampling

29. Advantages & Disadvantages
 Simple,cost-efficient,enables access to hard to find population.
 Works well when members know each other.
 Cons:
 Fate of study depend on first recruitment
 Cant control number of members recruited
 Misses out on the isolated ones
 Representativeness??
 Interviewer bias.

30. Solutions
 Key informant sampling:
 Involves speaking to knowledgeable person.eg. Rehab
centre councellor .
 Target sampling: done in 2 stages
a) Map the target population
b) Recruit pre-specified numbers of participants from each
site identified by ethnomapping.

32. IV- Combination or Mixed Purposeful Sampling
 Combines two or more strategies listed above.
 This type of sampling meets multiple interests and needs.

33. Convenient, accidental or haphazard Sampling
 A. Captive Sample
 B. Volunteer Sample

34. Convenient sampling
 Selects cases based on ease of accessibility.
 Argument: Equivalent to simple random sampling.
 Eg :people in street interview.

35. Advantages of convenient sampling
 This strategy saves time, money, and effort(quick,low cost
hassle free,no rules)
 In pilot studies,gives data and trends of pop. without
complication of using a randomized sample.

36. Disadvantages of convenient sampling
 Not representative of the population which leads to low external validity.
 Systematic bias : This refers to a constant difference between the results
from the sample and the theoretical results from the entire population. This
stems from over or under representation which leads to skewed results.
 Because the probability of inclusion in the sample is unknown for each
respondent, none of the reliability or sampling precision statistics can be
calculated.
 This strategy may yield information-poor cases

37. Volunteer sampling
 There is no fixed line of difference
 There is no sampling frame
 People are self motivated and volunteer

38. Disadvantages of volunteer sampling
 Result of study totally depends on people who
volunteered
 Cant compare as it cant be determined that those who did
not volunteer , to what extent differed from those who
volunteered.

39. Purposeful Random Sampling
 This strategy adds credibility to a sample when the
potential purposeful sample is larger than one can handle.
 It uses small sample sizes, thus the goal is credibility, not
representativeness or the ability to generalize.
 Ex:select 10 out of 300 drug addicts in rehab.

40. Stratified Purposeful Sampling
 Focuses on characteristics of particular subgroups of
interest; facilitates comparisons.
 This strategy is similar to stratified random sampling
(samples are taken within samples), except the sample
size is typically much smaller.
 In stratified sampling you “stratify” a sample based on a
characteristic.
 The main goal of this strategy is to capture major
variations (although common themes may emerge).

41. Paradigmatic Case Sampling
 A case is “paradigmatic” when it is considered the
exemplar for a certain class.
 For example, if one wanted to study the management of
professional sports teams, the paradigmatic case in hockey
of a successful franchise would be the Montreal
Canadians; for baseball it would be the New York
Yankees.

42. Stakeholder Sampling
 Particularly useful in the context of evaluation research
and policy analysis, this strategy involves identifying who
the major stakeholders are who are involved in designing,
giving, receiving, or administering the programme or
service being evaluated, and who might otherwise be
affected by it.

43. Expert sampling
 Expert sampling involves the assembling of a sample of persons
with known or demonstrable experience and expertise in some area.
Often, we convene such a sample under the auspices of a "panel of
experts." There are actually two reasons you might do expert
sampling.
 First, to get the the views of persons who have specific expertise. In
this case, expert sampling is essentially just a specific subcase of
purposive sampling.
 Second: Evidence of validity.

44. Contd.
Advantage:
 The advantage of doing this is that you aren't out on your
own trying to defend your decisions -- you have some
acknowledged experts to back you
Disadvantage:
 The disadvantage is that even the experts can be, and
often are, wrong

45. Quota sampling
 Non-probability version of stratified sampling
 Characteristics chosen are mutually exclusive and isolated
prior to sampling
 A quota is fixed,no randomization,no list used.
 May or may not be representative of population.

46. Quota types
 Proportional &non-proportional
 Interlocked and non interlocked.

47. Advantages and disadvantages
 Pros :
 Quick and cheap
 Allows study of traits and characteristics of subgroups and
also the relation between them
 Cons :
 Introduction of unknown bias
 Difficult to choose the variables as some may be highly
redundant.

48. Famous mistake of quota sampling

49. How do purposive and quota sampling differ?
 Purposive and quota sampling are similar in that they both
seek to identify participants based on selected criteria.
 Quota sampling is more specific with respect to sizes and
proportions of subsamples, with subgroups chosen to
reflect corresponding proportions in the population.
 Studies employ purposive rather than quota sampling
when the number of participants is more of a target than a
steadfast requirement – that is, an approximate rather than
a strict quota.

50. Biases
 Sampling bias
 Systematic bias
 Interviewers bias
 Observers bias.
 Ethical consideration .

51. Summary
 Sampling: a)Probabilistic
b)Non-probabilistic
 Non-probabilistic sampling used in qualitative research .
 Broadly categorized into: Purposive
convenient

52. References
 From Lisa M. Given (Ed.) (2008). The Sage Encyclopedia of Qualitative Research
Methods. Sage: Thousand Oaks,CA, Vol.2, pp.697‐698.
 K. Sabin, HIV Department, World Health Organisation, 20 avenueAppia, Geneva
27, Switzerland.
 SOCIOLOGICAL METHODS & RESEARCH, Vol. 10 No. 2. November 1981
141-163
 Social Problems, Vol .44,No.2 May 1997
 http://hdl.handle.net/10125/227
 Ethnobotany Research & Applications 5:147-158 (2007)
 Discussion Draft: Considerations and Recommendations Regarding the Use of
Judgmental Sampling in Soil Investigations
 Krista J. Gile and Mark S. Handcock. Respondent-driven sampling: An assessment
of current methodology. Sociological Methodology, 40:285–327,2010. URL
http://arxiv.org/abs/0904.1855v1.
 Journal of Mixed Methods Research 2007; 1; 77Charles Teddlie and Fen Yu
 Respondent driven sampling :A new approch to study hidden
population,Heckathon.

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