1. What is Qualitative Sample Size Calculation?

Qualitative sample size determination focuses on achieving data saturation rather than statistical power. It estimates the number of participants needed to reach thematic completeness in qualitative research studies.

2. How Does the Calculator Work?

The calculator uses the saturation-based formula:

Where:

• \( n \) — Estimated sample size (unitless)
• \( 10-30 \) — Participants per category range
• Categories — Qualitative themes or groups being studied

Explanation: The calculation is based on achieving data saturation, where additional participants no longer provide new information or themes.

3. Importance of Sample Size in Qualitative Research

Details: Appropriate sample size ensures comprehensive understanding of phenomena while avoiding unnecessary data collection. It balances depth of insight with practical research constraints.

4. Using the Calculator

Tips: Enter the number of anticipated categories or themes in your study and select the complexity level based on your research scope and depth requirements.

5. Frequently Asked Questions (FAQ)

Q1: What is data saturation?
A: Data saturation occurs when collecting additional data no longer provides new insights or themes, indicating comprehensive understanding has been achieved.

Q2: Why the range of 10-30 per category?
A: This range accommodates different research complexities - simple studies may saturate with 10 participants per category, while complex phenomena may require up to 30.

Q3: Can I use this for all qualitative methods?
A: This calculator is most appropriate for thematic analysis, grounded theory, and phenomenological studies. Some methods like case studies have different sampling considerations.

Q4: What if I don't know the number of categories?
A: Estimate based on literature review or pilot study. Qualitative research often involves iterative refinement of categories during data collection.

Q5: Is this sample size fixed?
A: No, qualitative sampling is often flexible. Use this as a starting point and adjust based on actual data saturation during your study.