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Clinical trial methodology, biostatistics, and study design guidance
Passed 15 of 22 test cases with the skill, and 12 of 22 without it.
and 2 more in the full report
3 fixed12 passed either way7 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 3 test cases the skill fixed. Same model, same prompt, with and without the skill.
Write a Python function to compute the sample size for a two-sample comparison of continuous means given minimum clinically important difference delta and pooled standard deviation sigma. What function name and dictionary key structure should be provided?
| Checked | Without skill | With skill |
|---|---|---|
| Names the function sample_size_two_means. | Missed | Passed |
| Returns dictionary key n_per_group_1. | Missed | Passed |
| Returns dictionary key total. | Missed | Passed |
The instructions your model reads when the skill loads.
A skill for designing and analyzing clinical trials, covering study design selection, sample size calculation, randomization methods, interim analysis, survival endpoints, and regulatory considerations. Essential for pharmaceutical researchers, biostatisticians, and clinical scientists.
| Phase | Objective | Typical N | Duration | Primary Endpoints |
|---|---|---|---|---|
| Phase I | Safety, dose-finding | 20-80 | Months | MTD, DLT, PK profile |
| Phase II | Efficacy signal, dosing | 100-300 | 1-2 years | Response rate, biomarker |
| Phase III | Confirmatory efficacy | 300-3,000+ | 2-4 years | OS, PFS, clinical outcome |
| Phase IV | Post-marketing surveillance | 1,000+ | Ongoing | Safety, real-world effectiveness |
Parallel Group (most common Phase III):
R --> Treatment A --> Outcome assessment
R --> Treatment B --> Outcome assessment
Crossover:
R --> Treatment A --> Washout --> Treatment B --> Outcome
R --> Treatment B --> Washout --> Treatment A --> Outcome
Factorial (2x2):
R --> Drug A + Drug B
R --> Drug A + Placebo B
R --> Placebo A + Drug B
R --> Placebo A + Placebo B
Adaptive:
Stage 1: Enroll n1 patients --> Interim analysis
Stage 2: Modify design (dose, sample size, arm dropping) --> Continue
test cases passed, vs 12 / 22 without
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