1. Biostatistics Support for Medical Student Research (MSR) Projects Allen Kunselman Division of Biostatistics and Bioinformatics Department of Public Health Sciences Penn State College of Medicine

2. MSR Process for Biostatistics Support l Not all MSR projects require a biostatistics consultation, but support is available l Limited free biostatistics support l Student is expected to do their own data collection and analysis with advice from statistician l Request biostatistics support well in advance of any deadline l In general, don’t procrastinate

3. Medical Student Research Process for Biostatistics Support l Complete the Department of Public Health Sciences (PHS) consultation request form at: http://app-phs.hmc.psu.edu/walkin2/forms/walkin_form.cfm l A meeting will be arranged and the student will receive statistical advice from the assigned statistical consultant l If at all possible, have your advisor attend the meeting l After the statistical consultant agrees with the proposed design and analysis, the student or statistical consultant will place the student's MSR Approval Form in Allen Kunselman's mailbox for a signature and the form will be returned.

4. 4 Reasons Why Investigators Seek A Statistician’s Collaboration l Advisor/mentor told them to do so l Their study did not show significance l Abstract or manuscript was rejected n They want the statistician to “work some magic” and resurrect their study l Reviewer of manuscript or grant told them to seek statistical advice l The investigator has planned and designed the study, conducted the experiment and collected the data, but now has no clue how to analyze it.

5. 5 Reasons Why Investigators Seek A Statistician’s Collaboration l Statistician viewed as a “necessary evil” needed in order to get sample size and analysis plan to appease the Internal Review Board (IRB) or potential grant/manuscript reviewers l Good experience collaborating with statisticians in the past n The statistician helped get a grant funded, manuscript published, results interpreted, etc. l Ideally, while the study is still in the planning and design phase, they seek a statistician because they really value the statistical advice and collaboration.

6. 6 http://statswithcats.files.wordpress.com/2012/02/statistician.jpg

7. Statistician: What My Collaborators Think I Do

8. 8 What can a Statistician Provide l Clarification of study objective n With respect to clinical trials: u Superiority: efficacy of treatment E is greater than that of treatment C –C can be a placebo or an active control u Non-inferiority: within a certain margin, efficacy of treatment E is at least as good as that of active control treatment C u Equivalence: within a certain margin, efficacy of treatment E is the same as that of active control treatment C

9. 9 What can a Statistician Provide l Experimental Design n Completely Randomized n Randomized Complete Block n Latin Square n Incomplete Block n Split-Plot n Factorial n Crossover n Bayesian n Adaptive

10. 10 What can a Statistician Provide l Sample size and power n Scientifically Meaningful Effect u Study must be “big enough” to statistically detect a scientifically (clinically) meaningful effect. u Study must not be “too big” where an effect of little scientific importance is nevertheless statistically detectable. n Money, Money, Money u Undersized study wastes resources and money by not having the capacity to produce useful (definitive) results. u Oversized study uses more resources and money than necessary.

11. 11 What can a Statistician Provide l Sample size and power (continued) n Ethical Issues u Undersized study exposes subjects to potentially harmful treatments without advancing knowledge. u Oversized study exposes more people than necessary to a potentially harmful treatment or denies a potentially beneficial treatment. n Grant reviewers (and IRBs) are looking for sample size and power considerations, especially for prospective studies!

12. 12 What can a Statistician Provide l Explicit definition of primary and secondary outcomes l Identify potential sources of random error and bias l Randomization l Blinding methods l Interim analysis and stopping rules l Methods for handling missing data

13. 13 What can a Statistician Provide l Consideration for potential confounders and effect modifiers l Statistical data analysis l Interpretation l Reporting and graphics l Reproducible analysis l Data collection, management, monitoring, and archiving

14. 14 Keys to Successful Collaboration: A Two-Way Street l Involve statistician at beginning of project (planning/design phase) l Specific objectives l Communication n avoid jargon n willingness to explain details

15. 15 Keys to Successful Collaboration: A Two-Way Street l Respect n Knowledge n Skills n Experience n Time l Embrace statistician as a member of the research team l Fund statistician on grant application for best collaboration n Most statisticians are supported by grants, not by Institutional funds

16. 16 Symbiotic Relationship for Investigator and Statistician l Investigator: scientific knowledge of the disease, outcomes, device, etc. l Statistician: technical skills to incorporate investigator’s scientific knowledge into an appropriate study design and analysis plan l In short, statisticians are not the enemy! Statisticians are there to contribute and support investigator research in order to obtain valid results.