1. Dr Carol Hawley, Dr Tom deBurgh, Colonel Robert Russell, Andrew Mead
Traumatic Brain Injury Among British Armed Forces Serving in Iraq and Afghanistan: Data from JTTR
Dr Carol Hawley, Dr Tom deBurgh, Colonel Robert Russell, Andrew Mead

2. Joint Theatre Trauma Registry
Unique Access to JTTR
Records every military casualty killed or injured on duty and seen by the Trauma team
Records kept from 2003 at start of Iraq War (2440 casualties to Sept. 2011)
How and where injured, clinical information, treatment given
Predictor Variables: Injury severity scores: TRISS, AIS, NISS, ASCOT
Outcome Variables: Fatality/Survivor; Hospital, Rehabilitation, Return to Duty

3. History of the paper
Analysis as per study protocol and submission to Journal of Head Trauma Rehabilitation January 2013
Returned with comments from ‘Statistical’ Reviewer. Wanted different methods and asked us to use tests never heard of. “Point- biserial correlations, the 2-step method of Belsley et al. Use BIC and AIC to choose the best injury severity variable.”
Statistical Seminar !! Discussion with Andrew
Re-did analysis according to ‘Stats’ Reviewer request. Resubmitted V2

4. History continued...
Returned from ‘Statistical’ reviewer – still not happy, wants different analysis and different tests......
Another Statistical Seminar – chat with Sandy – arranges one-to-one with Andrew
We share the database and work on the latest set of ‘Stats’ Reviewer requirements.
Andrew added as co-author and writes detailed explanation of statistical analysis (simple logistic regression and multiple logistic regression)
Resubmitted V3

5. Continued...
‘Stats’ reviewer still not happy. Editor steps in and recommends we remove the multiple regression to pacify the reviewer.
Andrew writes response to ‘Stats’ Reviewer. Revise and resubmit V4.
ACCEPTED !
But, a compromise and shows how a ‘statistical’ reviewer can force researchers to alter the methods prescribed in a study protocol. Without this statistical seminar series and Andrew’s help doubt would have succeeded.
Publication soon, meeting University Press Officer later today, high impact expected.

6. Statistical Consultancy and Collaboration
Understand aims of study and dataset
Explore and explain reviewers suggestions
‘point biserial correlation’ – correlation where one variable is binary, but calculations identical to standard Pearson product-moment correlation!
‘logistic regression’ – takes correct account of distribution of the response (binary – survival)
‘issues with multicollinearity (Belsley 2-step method)’ – SPSS does exactly what reviewer wanted, but not explicit in output!

7. Statistical Consultancy and Collaboration
Re-analysis considering a wider range of models and providing more detailed interpretation
Further exploration of data
Identification of data inconsistencies, effectively as a result of ‘missing’ observations
Refining of records to be included
More detailed description of data analysis approaches
Identification of tests used to select models, using output produced by SPSS
Using available output to ‘better’ explain the analysis performed

8. Interactions with Editors and Reviewers
Compromise often needed on statistical issues in publications
Reviewers often have a limited (‘biased’) view on appropriate approaches
Not necessarily based on statistical expertise but often on past experience!
Possibly based on what their ‘favourite’ package produces
Different packages produce different outputs, but generally perform the same analysis!
Journals (Editors) are often reluctant to publish ‘novel’/unusual statistical approaches
Correct/appropriate methods applied here, but ‘too statistical’ for journal?
Reviewers view accepted above statistical expertise of co-author?