All examples for Power Analysis Sample Size Calculator

Sample Size for Clinical Intervention Grant Proposal

Calculate sample size for a clinical intervention study with medium effect size (d=0.5), 80% power for grant proposal, accounting for 20% participant attrition with ready-to-use methodology language.

Input

What you provide to the skill

Planning a clinical intervention study with expected medium effect size (Cohen’s d=0.5). Need 80% power for grant proposal. Expecting 20% participant attrition.

Output

What the skill generates for you

SAMPLE SIZE FOR GRANT PROPOSAL

Study Design: Independent samples t-test
Effect Size: d = 0.5 (medium)
Power: 80%
Alpha: 0.05

Required Sample Size: 64 per group (128 total)

Accounting for 20% attrition: Recruit 160 participants (80 per group)


Sensitivity Analysis

| Effect Size (d) | Interpretation | N per Group | Total N | Total with 20% Attrition |
|—————–|––––––––|———––|———|–––––––––––––||
| 0.2 | small | 394 | 788 | 986 |
| 0.3 | small | 176 | 352 | 440 |
| 0.5 | medium | 64 | 128 | 160 |
| 0.7 | medium | 34 | 68 | 85 |
| 0.8 | large | 26 | 52 | 65 |


Grant Proposal Language

Recommended text for methodology section:

“Based on literature review suggesting a medium effect size (Cohen’s d = 0.5) for similar clinical interventions, we conducted an a priori power analysis for an independent samples t-test with alpha = .05 and power = .80. Results indicated that a minimum sample size of 64 participants per group (128 total) is required to detect the anticipated effect. To account for an expected 20% participant attrition rate, we will recruit 160 participants (80 per condition), ensuring adequate power even with expected dropout.”


Recommendations

Feasibility: 160 participants is a reasonable target for most clinical intervention studies
Conservative approach: If pilot data or effect size estimates are uncertain, consider recruiting additional buffer beyond 20% attrition
Pre-registration: Register your study and analysis plan (including this sample size calculation) before data collection begins
Monitor attrition: If dropout exceeds 20%, consider supplemental recruitment to maintain power