How Are Cases or Subjects in a Study Chosen in the Mixed

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The Answer is In a mixed methods approach, which combines both quantitative and qualitative research methods, the selection of cases or subjects for a study is guided by the research questions and objectives, as well as the specific design of the study. Here are some considerations for choosing cases or subjects in a mixed methods study:

1. **Purposeful Sampling**: In qualitative components of mixed methods research, researchers often use purposeful sampling to select information-rich cases that can provide in-depth understanding. This means choosing participants who have specific characteristics or experiences relevant to the study's research questions.

2. **Random Sampling**: In the quantitative components, researchers might use random sampling to select subjects in a way that allows for generalization of results to a larger population. This involves randomly choosing participants from a larger pool so that every individual has an equal chance of being included in the study.

3. **Stratified Sampling**: To ensure representation across key subgroups, researchers may use stratified sampling. This involves dividing the population into subgroups (strata) and then randomly selecting samples from each stratum.

4. **Convenience Sampling**: Sometimes, due to practical constraints, researchers might choose subjects who are readily available or convenient to access. While this is not ideal for generalizability, it can be acceptable depending on the research goals and the nature of the study.

5. **Theoretical Sampling**: In studies using a grounded theory approach within their qualitative component, theoretical sampling is used. This means that the selection of subjects is guided by the emerging theory; researchers make decisions about where to find data next based on their developing understanding.

6. **Snowball Sampling**: Researchers may also use snowball sampling, particularly when looking for subjects with specific characteristics or experiences that are hard to find. Current study participants refer future participants from among their acquaintances.

7. **Quota Sampling**: This non-probability sampling technique is used to ensure that the sample represents certain characteristics of the population. Researchers decide on the exact proportions of certain types of individuals to include.

8. **Maximum Variation Sampling**: To capture a wide range of perspectives, researchers may seek maximum variation in their sample. This involves intentionally seeking out subjects with diverse characteristics related to the topic of interest.

9. **Nested Sampling**: In some mixed methods designs, researchers might have a nested sample where a subset of the quantitative sample is also included in the qualitative sample. This allows for deeper exploration of certain phenomena or results.

10. **Integrated Sampling**: In some advanced mixed methods designs, sampling decisions are made to facilitate integration at the design level. For example, the same individuals might be included in both qualitative and quantitative parts of the study, or the qualitative sample might be drawn from different levels of a quantitative variable (e.g., high, medium, and low scorers).

The choice of sampling strategy in mixed methods research is crucial and should align with the study's theoretical framework, research questions, and practical considerations such as time, resources, and access to participants. Researchers must also consider ethical issues, ensuring that the sample is selected fairly and that participants are treated with respect throughout the research process.

How Are Cases or Subjects in a Study Chosen in the Mixed

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