Power, Sample Size, and Feasibility in Real-World Research
Decisions about power and sample size are often treated as purely technical requirements, boxes to check or formulas to satisfy. In real-world research, however, these decisions are rarely abstract or idealized. They are shaped by feasibility, access, timelines, and ethical constraints.
Evaluators generally understand this. What they look for is not perfection, but whether power and sample size decisions are reasonable, transparent, and defensible given the research context. Understanding how these decisions are evaluated can help researchers navigate critique more effectively and avoid unnecessary redesign.
Why Power Is Often Misunderstood
Power analysis is frequently framed as a requirement to achieve a specific numerical threshold. While statistical power matters, evaluators are rarely asking whether a study meets an idealized standard in isolation.
Instead, they are asking whether the study was designed with an understanding of uncertainty, variability, and practical constraints. Problems arise when power is treated as a purely mechanical calculation rather than as part of a broader design rationale.
Overemphasis on formulas without context can actually weaken defensibility, particularly when assumptions are unrealistic or poorly explained.
Sample Size as a Design Decision, Not a Formula
Sample size is not simply an output of a power calculation. It is a design decision that reflects trade-offs among analytic goals, feasibility, and available data.
In applied research, sample sizes are often constrained by access to participants, institutional data structures, or ethical considerations. Evaluators typically recognize these constraints and do not expect researchers to exceed what is realistically attainable.
What they do expect is clarity. Researchers should explain how sample size was determined, what assumptions were made, and how limitations affect interpretation.
Feasibility Is Not a Weakness
Many researchers hesitate to foreground feasibility concerns, fearing they signal methodological weakness. In practice, the opposite is often true.
Explicit discussion of feasibility demonstrates that a study was designed intentionally and responsibly. Evaluators are often more concerned when feasibility constraints are ignored than when they are openly acknowledged.
Studies that are theoretically ambitious but practically unrealistic tend to raise more concern than those that are appropriately scoped and well executed.
Interpreting Power-Related Critique
When evaluators raise concerns about power or sample size, they are often signaling uncertainty about what the study can reasonably detect or support.
Rather than immediately increasing sample size or adding analyses, it can be helpful to ask the following questions:
Is the critique about overinterpretation?
Is the critique about unclear assumptions?
Is the critique about mismatch between claims and design?
Addressing these issues through clearer explanation or more cautious interpretation is often sufficient.
Aligning Claims With Design
One of the most effective ways to strengthen defensibility around power and sample size is to ensure that claims are aligned with what the study can support.
This may involve narrowing conclusions, emphasizing estimation over hypothesis testing, or framing findings as exploratory rather than confirmatory. Such adjustments do not weaken a study. They strengthen credibility.
Evaluators are generally receptive to studies that demonstrate restraint and transparency in interpretation.
Power Across Different Research Contexts
Expectations around power and sample size vary across contexts, but the underlying principles remain consistent. Dissertation committees, grant panels, journal reviewers, and institutional stakeholders all tend to ask whether the study’s design is appropriate for its goals and constraints.
Researchers who approach power and sample size as part of a coherent design narrative, rather than as isolated requirements, are often better positioned to navigate these different settings.
A Final Thought
In real-world research, power and sample size decisions are rarely ideal. What matters most is whether those decisions are made thoughtfully, explained clearly, and interpreted responsibly.
Defensibility emerges not from maximizing numbers, but from aligning design, feasibility, and claims in a way that evaluators can understand and support.
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If you are navigating power, sample size, or feasibility questions, or responding to critique related to study design, structured guidance can be helpful.
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