IEG Stats Clinic

We can all get stuck and face statistical issues at times. The IEG Stats Clinic provides collegial advice on statistical analyses for researchers and PhD students. For Master student projects, we ask that the supervisor (with or without the Master student) contacts us, at least initially.

Welcome!

What can you expect to get?

We provide a forum for discussion and advice and can, hopefully, point you in productive directions or help you interpret the results of your analyses. We also welcome discussions about issues relating to experimental or sampling design, during the planning stage of your project.

What will you not get?

We will not run the analyses for you or debug all your code.

Who is this for?

All researchers at IEG, including PhD students, are welcome. In order to avoid misunderstandings, we ask that PhD students first discuss the issue at hand with their supervisor. For Master students projects, we ask that the supervisor (with or without student) contacts us. For Master or PhD theses requiring a lot of hands-on support we would prefer that a suitable colleague is asked to be co-supervisor from the beginning of the thesis.

Who do I contact?

Please feel free to e-mail anyone of us for an appointment– our approximate experience is listed below.

David Berger: general statistical issues, experimental design, general/ized linear models, MCMC fitting, quantitative genetics, experimental evolution, implementation of analyses in R.

Gustaf Granath: general/ized linear models, meta-analysis, multivariate statistics, structural equation modelling, spatial statistics.

Arild Husby: general/ized linear models, statistical genetics (quantitative genetics, association studies, linkage disequilibrium etc).

Sophie Karrenberg: experimental design, general basic statistics, linear mixed models, implementation of analyses in R.

Martin Lind: experimental design, general/ized linear models, survival analysis.

Pascal Milesi: general statistical issues, experimental design, general/ized linear models, association studies (GWAS, GEA), multivariate analysis, implementation of analyses in R.

Douglas Scofield: general basic statistics, linear and nonlinear models other than GLMMs, nonparametric statistics, experimental design, statistical genetics, bioinformatics, implementation of analyses in R.

Joining the stats clinic

If you would like to join the stats clinic and provide support for colleagues, please contact Sophie Karrenberg.