Biostatistics
Study design and data analysis aligned with regulatory standards.
Sample size planning
- Power calculations:
Statistical power and effect size determination - Study design optimization:
Randomization strategies and adaptive planning - Regulatory compliance:
FDA/EMA statistical requirements and submission planning
- Power calculations:
Interim and final analysis
- Statistical programming:
SAS, R programming for regulatory submissions - Efficacy and safety analysis:
Primary/secondary endpoints and adverse event profiling - PK modeling:
Pharmacokinetic analysis and bioequivalence studies
- Statistical programming:
Meta-analysis and indirect comparisons
- Network meta-analysis:
Multiple treatment comparisons and evidence synthesis - Real-world evidence:
Observational study analysis and comparative effectiveness - Health economics:
HEOR analysis and cost-effectiveness modeling
- Network meta-analysis:
