Statistical Thinking in Biomedical Research: Agenda for a Short Course or Research RetreatICUD


  1. Present the biostatistical concepts that researchers need in order to evaluate the results of published clinical studies, to design and analyze studies, and to collaborate effectively with methodologists
  2. Illustrate how biostatistical and epidemiologic principles affect all phases of the study, including choosing an outcome measure, developing procedures for collecting accurate and complete data and summarizing study results
  3. Introduce participants to fundamental concepts in statistical inference to be able to recognize problems of bias and imprecision that can lead to misleading or uninformative results
  4. Present approaches for choosing response variables and clinical endpoints
  5. Learn about levels of evidence provided by different types of studies
  6. Understand underlying concepts, not computations
  7. To learn about existing biostatistical resources at Vanderbilt and how to build division-specific resources


  1. What does biostatistics have to offer to biomedical research?
  2. Fundamentals of statistical inference
  3. Study design issues
    1. Sources of bias
    2. Measurement issues and choice of response variable
    3. Efficiency, power, and precision
    4. Maximizing use of a given number of animals
    5. Interpretability of findings
  4. Types of studies and role of randomization
  5. Pitfalls in interpreting statistical results
  6. Descriptive statistics
  7. Measuring change
  8. Reproducible research
  9. How to collaborate with biostatisticians
  10. Biostatistical resources

Topic revision: r2 - 17 May 2006, AyumiShintani

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