Service
Support for researchers
You want to stay in control of your own analysis, but be certain the method holds. I support you at the moments that matter: the choice of model, the difficult calls, and the response to reviewers.
Who it is for
This service is for those who do the analysis themselves — by preference, by academic requirement or by budget — and who want a statistician beside them rather than instead of them.
- PhD students mid-thesis, in any discipline
- Postdocs preparing a submission
- Doctors running a clinical or retrospective study
- Master's students with a quantitative component
- Research teams with no dedicated statistician
- Researchers facing a harsh review report
The problem it solves
In most academic paths, statistics is taught once, early on, using clean examples. Then you find yourself alone with real data: unbalanced groups, missing values, repeated measures, variables that follow no normal distribution.
The classic mistake is not miscalculating. It is choosing a test designed for a different situation than yours, and only realising it when the reviews come back — once collection is over and it is too late to change the study design.
Support up front is almost always cheaper than repair downstream.
- You are torn between several tests and cannot decide
- Your supervisor asks you to "justify the model"
- A reviewer demands a correction for multiple testing
- You do not know how to handle your missing data
- Your results are significant but you doubt they hold
- Your jury will ask about method and you want to be ready
What you get
The aim is not only to unblock the current point, but to make you self-sufficient on the next ones.
- Test justifications you can lift straight into your methods section
- The model that fits the structure of your data
- A critical review of your statistics section
- Reasoned answers to reviewers' comments
- Your software output interpreted, line by line
- Your R scripts reviewed, corrected and commented
How it works
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First contact
You set out your project and where it is stuck. I tell you frankly whether I can help.
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Scoping
We agree on the format: one-off on a single question, or ongoing across the study.
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Working together
Working sessions on your data, with the explanations that go with them. You keep control.
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Autonomy
You leave with the written justification and the understanding needed to defend your choices.
Concrete examples
The most frequent requests, as methodological illustrations.
Choosing the right test
Two groups, small samples, skewed distribution: t-test, Wilcoxon, or a permutation test? A reasoned, checkable decision.
Repeated measures
The same subjects measured at several time points. Standard tests become invalid; you need a model that accounts for the dependence.
Answering a reviewer
"The statistical analysis is inadequate." A precise diagnosis of the objection, the correction, and the written response.
Correcting for multiple testing
Twenty comparisons, and one comes out "significant" by chance. Which correction to apply, and when it is not needed.
Missing data
Dropping incomplete rows often biases the results. Choosing between complete-case analysis, imputation, or a robust model.
Preparing your defence
Anticipating a jury's methodological questions and answering them without contradicting yourself.
Frequently asked questions
When is the best time to contact you?
Do you run the analysis for me?
Can I consult you about a single question?
Do you work with software other than R?
My field is not medical. Is that a problem?
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Describe your need in a few lines, or book a first no-commitment call. I will tell you straight if I am the right person for it.