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Experimental and Observational Study Design

Improving experimental designs, convincing conclusions and more revealing data analyses.

Biostatisticians focus on study design and planning as their most critical contribution to collaboration. Frequent collaborative interactions lead to improved experimental designs, convincing conclusions and more revealing data analyses.

Areas of expertise in design, planning and analysis include:

  • Evaluation of diagnostic techniques
  • Laboratory experimental design
  • Bioassay experiments
  • Pharmaco-analytics
  • Robust mixed modeling for experimental data with dependency structure
  • Causal inference for observational study designs
  • Complex modeling for longitudinal and other observational studies
  • Statistical programming
  • Re-estimation of sample size
  • Multiple hypothesis testing strategies
  • Propensity Score Matching
  • Training and validation for feature selection

For more information on study design, send an email to ccts-biostat@osumc.edu.

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Acknowledging CTSA grant support in publications
Biostatistics Services

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