How to Justify Your Sample Size in a Dissertation Proposal
Sample size questions are among the most common sources of anxiety in dissertation proposals. Students worry that their sample is too small, that reviewers will demand unrealistic recruitment targets, or that they need a “perfect” power calculation to satisfy their committee.
In reality, committees are not looking for a large number. They are looking for a defensible rationale. This post explains how to justify sample size in a way that demonstrates methodological rigor and feasibility.
What Committees Are Evaluating
When committees question sample size, they are usually evaluating three things:
Whether the sample is large enough to answer the research question with reasonable precision.
Whether recruitment is realistic within your timeline and access constraints.
Whether analytic complexity matches the available data.
The issue is usually always alignment, not magnitude.
Quantitative Studies: Power and Practical Constraints
For quantitative designs, justification often involves power analysis. A clear explanation should identify:
• The expected effect size
• The chosen alpha level
• The desired statistical power
• The statistical test used
However, power analysis should not be treated as a mechanical exercise. Effect size assumptions should be grounded in prior literature, pilot data, or theoretically meaningful thresholds.
At the same time, feasibility matters. If the ideal power analysis suggests 800 participants but your accessible population is 300, that tension must be addressed explicitly. Committees appreciate transparency about constraints more than unrealistic projections.
Qualitative Studies: Saturation and Depth
For qualitative research, justification looks different. Instead of statistical power, the focus is on conceptual saturation, depth of inquiry, and the ability to meaningfully analyze cases.
A strong justification explains:
• Why the proposed number of interviews or cases is sufficient to capture variation
• How participants will be selected
• How saturation will be assessed
The argument centers on analytic depth rather than numerical thresholds. You can also introduce the possibility that your recruitment may end early (if saturation is achieved using less participants) or extend to more individuals (if you haven’t yet achieved saturation by the end of your last interview).
Mixed Methods and Complex Designs
In mixed methods or multilevel studies, sample size justification must address each analytic component separately. For example, a survey component may require power analysis, while interview subsamples require saturation-based reasoning.
Clarity about which sample supports which analysis prevents confusion.
What Committees Actually Want
Committees do not expect perfection. They expect reasoning. A strong sample size section demonstrates:
• Awareness of statistical or conceptual requirements
• Alignment between sample and analytic strategy
• Realistic recruitment planning
• Transparency about limitations
When those elements are present, even modest samples can be defensible.
Interested in Support?
If you are developing a proposal and unsure how to justify your sample size or respond to committee feedback about power or feasibility, structured guidance can be helpful.
Learn more about my approach to dissertation consulting or schedule a consultation.
