Qualitative Sampling Strategies
Qualitative Research
seeks to answer a question / explore a phenomena
collects evidence
produces findings that were not determined in advance
generalizable & applicable beyond immediate study
from perspective of local population of involvement
culturally specific
values
opinions
behaviours
social contexts
Methods (semi-structured)
Participant Observation
In-Depth Interviews
Focus Groups
collects data on naturally occurring behaviours in their usual context / setting
collects data on cultural norms of a group
collects data on an individual's personal history, perspective, experience
Forms
field notes
audio / video recordings
transcripts
Describes & Explains
variation
relationships
individual experiences
group norms
open-ended
textual & iterative
Sample: subset of population selected for any given study
Sufficiency
Explanation
Most Common Non-Probability Sampling Methods
research objectives and characteristics of study population (such as size and diversity) determine which and how many people to select
2) Quota
3) Snowball
1) Purposive
definition: groups participants according to preselected criteria relevant to a particular research question
sample size: depend on resources and time available, as well as study's objectives. often determined on basis of theoretical saturation
definition: sometimes considered a type of purposive sampling; decide while designing the study how many people with which characteristics to include as participants - age, gender, class, marital status, profession, etc.
sample size: go into community and using recruitment strategies appropriate to the location, culture, and study population, find people who fit the criteria until quota is met
more specific than purposive sampling with respect to sizes and proportions of subsamples
definition: considered a type of purposive sampling; researchers rely on participant referrals and/or social networks to recruit members for study
sample size: find and recruit "hidden populations" and becomes larger along the way
Too Small
doesn't support redundancy
doesn't support theoretical saturation
Too Large
doesn't permit in-depth analysis
matter of judgement and experience
evaluate quality of information collected
understand the uses to which the information will be put against, the method employed, and the product intended
Principle of Saturation
sample size large enough to sufficiently describe the phenomenon of interest and address the research question
repetitive data
adding more participants to the study doesn't result in obtaining additional perspectives and/or information