Section of Biostatistics > Statistical advisory s...
Statistical advisory service at Rigshospitalet
What can we assist with
Any type of statistical problem in relation to planning a study, choosing and applying the appropriate statistical tools, and understanding results. This includes
- Study design (type of design and sample size)
- Statistical analysis (Choice of analysis, execution of analysis via dedicated statistical software, interpretation and reporting of results)
Note that we are only able to offer very limited help with dedicated data management such as data cleaning and data base programming
Who is eligible for help
Researchers and research groups at Copenhagen University Hospital and Glostrup Hospital.
PhD students and employees at the Faculty of Health and Medicinal Sciences are requested to use our regular advisory service :
How to get help
Write an email to RHemail@example.com
containing a brief description of your problem. Emails are handled on a weekly basis each Friday, so you can expect to receive a response to your request within a week.
How much help can you get
This is judged from a case to case basis entirely at the discretion of the statistical consultant handling your request. For larger commitments additional funding may be necessary.
If the consultant provides substantial input for a paper in terms of analyses, interpretation of results, and drafting of the paper, then coauthorship is only natural and expected. See also the Vancouver Protocol
Examples of specific questions
Question: I have conducted a two sided t-test, but a referee has asked for a non-parametric test in addition. What is this and how do I compute the test?
Question: We are planning an RCT and need to discuss power and statistical analysis plan.
Question: I cannot insert text on a plot created in SAS.
Question: I have conducted a logistic regression, but would like to discuss if I have interpreted the estimates correctly.
Question: We are planning to apply for funding for a larger study, but are in doubt about the best ways to describe and subsequently tackle the statistical challenges.