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Purposive Sampling
Purposive sampling in qualitative inquiry is the deliberate seeking out of participants with particular characteristics, according to the needs of the developing analysis and emerging theory. Because, at the beginning of the study, the researcher does not know enough about a particular phenomenon, the nature of the sample is not always predetermined. Often, midway through data analysis, the researcher will realize that he or she will need to interview participants who were not envisioned as pertinent for the study at the beginning of the project. For example, Martin (1998), in her study of sudden infant death syndrome (SIDS), discovered issues of control over the responsibility for these infants between the groups of first responders (emergency medical technicians and the firefighters) and realized that she would have to interview these professionals, extending her study beyond the interviews with parents, as originally perceived.
Types of purposive sampling are nominated or snowball sampling (in which participants are referred by members of the same group who have already been enrolled in the study) and theoretical sampling (in which participants are deliberately sought according to information required by the analysis as the study progresses).
In nominated or snowball sampling, the researcher locates a “good” participant and, at the end of the interview, asks the participant to help with the study by referring the researcher to another person who may like to participate in the study. Thus, sampling follows a social network. Nominated or snowball sampling is particularly useful when groups are hard to identify or may not volunteer or respond to a notice advertising for participants. It is a useful strategy when locating participants who would otherwise be hard to locate, perhaps because of shame of fear of reprisal for illegal activities, such as drug use; a closed group, such as a motorcycle gang; or those who have private behaviors or a stigma associated with a disease. Gaining trust with the first participant and allowing that person to assure the group that the research is “OK” provides access to participants who would otherwise be unobtainable.
The final use of a nominated sample is by researchers who are using theoretical sampling. They may use a form of nominated sample by requesting recommendations from the group for participants who have certain kind of experiences or knowledge needed to move the analysis forward.
Reference
- Analysis of Variance
- Association and Correlation
- Association
- Association Model
- Asymmetric Measures
- Biserial Correlation
- Canonical Correlation Analysis
- Correlation
- Correspondence Analysis
- Intraclass Correlation
- Multiple Correlation
- Part Correlation
- Partial Correlation
- Pearson's Correlation Coefficient
- Semipartial Correlation
- Simple Correlation (Regression)
- Spearman Correlation Coefficient
- Strength of Association
- Symmetric Measures
- Basic Qualitative Research
- Basic Statistics
- F Ratio
- N(n)
- t-Test
- X¯
- Y Variable
- z-Test
- Alternative Hypothesis
- Average
- Bar Graph
- Bell-Shaped Curve
- Bimodal
- Case
- Causal Modeling
- Cell
- Covariance
- Cumulative Frequency Polygon
- Data
- Dependent Variable
- Dispersion
- Exploratory Data Analysis
- Frequency Distribution
- Histogram
- Hypothesis
- Independent Variable
- Measures of Central Tendency
- Median
- Null Hypothesis
- Pie Chart
- Regression
- Standard Deviation
- Statistic
- Causal Modeling
- DISCOURSE/CONVERSATION ANALYSIS
- Econometrics
- Epistemology
- Ethnography
- Evaluation
- Event History Analysis
- Experimental Design
- Factor Analysis and Related Techniques
- Feminist Methodology
- Generalized Linear Models
- HISTORICAL/COMPARATIVE
- Interviewing in Qualitative Research
- Latent Variable Model
- LIFE HISTORY/BIOGRAPHY
- LOG-LINEAR MODELS (CATEGORICAL DEPENDENT VARIABLES)
- Longitudinal Analysis
- Mathematics and Formal Models
- Measurement Level
- Measurement Testing and Classification
- Multilevel Analysis
- Multiple Regression
- Qualitative Data Analysis
- Sampling in Qualitative Research
- Sampling in Surveys
- Scaling
- Significance Testing
- Simple Regression
- Survey Design
- Time Series
- ARIMA
- Box-Jenkins Modeling
- Cointegration
- Detrending
- Durbin-Watson Statistic
- Error Correction Models
- Forecasting
- Granger Causality
- Interrupted Time-Series Design
- Intervention Analysis
- Lag Structure
- Moving Average
- Periodicity
- Serial Correlation
- Spectral Analysis
- Time-Series Cross-Section (TSCS) Models
- Time-Series Data (Analysis/Design)
- Trend Analysis
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