[SFdS] Information du groupe BFA
WG Risk - Friday, February 26, 2021 - Prof. Marie-Abèle BIND

Dear All,

We have the pleasure, thanks to the support of the ESSEC IDS dpt, Institut des Actuaires, LabEx MME-DII, the group BFA of SFdS, and all ARLES (Aging Risks and their Long-term impact on the Economy and Society research project) partners to invite:

Prof. Marie-Abèle BIND
MGH Biostatistics Center &
Harvard Medical School, USA

Date and place: Friday, February 26, at 2:00 pm (Paris ) and 9:00 pm (Singapore)
Please note that we need to postpone the seminar to 2pm (instead of 12:30) as our invited speaker will talk from Boston.
To participate in the Working Group (via Zoom), please click here
Password/Code : WGRisk
.

“ 21st century causal inference that capitalizes on classical design of experiments and modern computing, illustrated with an epigenomic human experiment "

In randomized experiments, Fisher-exact p-values are available and should be used to help evaluate results rather than the more commonly reported asymptotic p-values. One reason is that using the latter can effectively alter the question being addressed by including irrelevant distributional assumptions. The Fisherian statistical framework, proposed in 1925, calculates a p-value in a randomized experiment by using the actual randomization procedure that led to the observed data. Here, we illustrate this Fisherian framework in a crossover randomized experiment. We focus on 10 epigenetic outcomes that illustrate important differences between the asymptotic and Fisher tests for the null hypothesis of no ozone effect. For some outcomes, the traditional p-value based on the approximating asymptotic Student's t distribution substantially subceeded the minimum attainable Fisher-exact p-value. For the other outcomes, the Fisher-exact null randomization distribution substantially differed from the bell-shaped one assumed by the asymptotic t test. Our conclusions: When researchers choose to report p-values in randomized experiments,
1) Fisher-exact p-values should be used, especially in studies with small sample sizes, and
2) the shape of the actual null randomization distribution should be examined for the recondite scientific insights it may reveal.


Kind regards,
Jeremy Heng, Olga Klopp and Marie Kratz
http://crear.essec.edu/working-group-on-risk
and Riada Djebbar (Singapore Actuarial Society - ERM)

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