Qualitative Sampling & Assumptions by Amber Atwater & Charlott Livingston for EDUC 5394

Theorists Glaser & Strauss Huberman Miles Morse Patten Patton Sandelowski

Almost all Qualitative Sampling is Purposive

Purposive Sampling Type of SamplingPurpose Maximum Variation Documents diverse variations and identifies important common patterns. Homogeneous Focuses, reduces, simplifies, and facilitates group interviewing. Critical case Permits logical generalization and maximum application of information to other cases. Theory based Find examples of a theoretical construct and thereby elaborate on and examine it. Confirming and disconfirming cases Elaborate on initial analysis, seek exceptions, looking for variation. Snowball or chain Identifies cases of interest from people who know people who know what cases are information-rich. Extreme or deviant case Learn from highly unusual manifestations of the phenomenon of interest. Typical caseHighlight what is normal or average.

Purposive Sampling Cont. Type of SamplingPurpose Intensity Information-rich cases that manifest the phenomenon intensely but not extremely. Politically important cases Attracts desired attention or avoids attracting undesired attention. Random purposeful Adds credibility to sample when potential purposeful sample is too large. Stratified purposefulIllustrates subgroups and facilitates comparisons. Criterion All cases that meet some criterion; useful for quality assurance. Opportunistic Follow new leads; taking advantage of the unexpected. Combination or mixed Triangulation, flexibility; meets multiple interests and needs. ConvenienceSaves time, money, and effort, but at the expense of information and credibility.

Random and Convenience Sampling

Sample Size Is Smaller Because:  They are more expensive  They are more time consuming  They involve a select group  Sometimes they are simply a case study

Saturation Sample size is often determined by the saturation point; the point at which no new information or relevance is given to the study. This is determined by using an iterative approach; moving back and forth (iterating) between the data collected and analyzing the findings to determine if it is the same information or new information.

Assumptions Epistemological assumptions- Researchers believe the best way to understand any phenomenon is to view it in its context or natural environment. Ontological Assumptions- Many qualitative researchers also don't assume that there is a single unitary reality apart from our perceptions. Since each of us experiences from our own point of view, each of us experiences a different reality

Doing research without taking into account the participants life experiences and personal views can skew the validity of the research.

Qualitative Data In depth interviews- it is assumed there is a questioner and one or more interviewees. Direct Observation- Broad phrase, the researcher does not actively question the subjects. Can include everything from field research where he lives in the place for a period of time gathering information to photographs depicting certain phenomenon.

Written Documents- Refers to existing documents such as books, articles, annuals or other texts. Written documents are usually analyzed with content analysis.

Qualitative Generalizations A good empirical generalization includes: ◦ Scope ◦ Precision ◦ Parsimony ◦ Usefulness ◦ And a link with theory

Scope Not all generalizations are the same Held under a wide range of conditions ◦ Sectors countries situations Ideally it should be fairly predictable and hold up in its domain but break down outside of it Usually unclear since it is only an approximation

Precision Description of a phenomenon that has been observed several or many times Modelers know there are many ways to describe some data and one factor for deciding which is best is precision. Statistical test do not help us choose between an approximate generalization and an invalid on. There is no generally accepted way of summarizing generalizations qualitatively

Parsimony “In scientific description, other things being equal ‘’less is more.”” Many of the major advances in science came from studies with similar scope and precision of previous studies but were on smaller and simpler scales.

Example Given: Classic cases are Kepler’s description of planetary motion using ellipses and Mendeleev’s periodic classification of the chemical elements. The power of a parsimonious description is first, its tractability, and second, that it omits most variables that might have mattered. This helps both prediction and the development of theory: thanks to Kepler, Newton knew that the orbit was elliptical whether the planet was large or small, red or white, near the sun or far, etc. ~Barwise

Usefulness Your theories should be able to adapt to a changing environment Should be practical now, even if it is on a small scale, not hopefully something that will be widely known and applied by everyone sometime in the future

Link with Theory Your idea or theory, according to Patrick Barwise, is better if it can be explained or supported by an already established theory. Your predictions can be consistent with the established theory and hopefully accounts for scope. By applying another theory on top of yours, especially if it is a commonly known theory, you are increasing the odds of background knowledge on the subject.

References Barwise, P. (1995). Good Empirical Generalizations. In Marketing Science, Vol. 14, No. 3 Part 2 of 2 Special Issue on Empirical Genrealizations in Marketing. (pp. G29-G35). London, England. Informs Glaser, B. & Strauss, A. (1967). The discovery of grounded theory: Strategies for qualitative research. Chicago: Aldine. Miles, MB. & Huberman, AM. (1994). Qualitative data analysis, second edition. Thousand Oaks, CA: Sage Publications. Morse, JM. (1991). Strategies for sampling. In JM Morse’s (JM Morse, Ed.), Qualitative Nursing Research: A Contemporary Dialogue (pp ). Newbury Park, CA: Sage Publications. Patten, M.L. (2009). Understanding research methods: An overview of the essential, seventh edition : Pyrczak Publishing. Patton, MQ. (2001). Qualitative research and evaluation methods, second edition. Thousand oaks, CA: Sage Publications. Sandelowski, M. (1995). Sample size in qualitative research. Research in nursing and health, 18,