Conference : From Controlled Trials to Big Data and Back

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XXXIst Conference of the Austro-Swiss Region (ROeS) of the International Biometric Society

 

 

From Controlled Trials to Big Data and Back

Lausanne, September 9-12, 2019

 

Statistical data analyses are sometimes classified as being either exploratory or confirmatory, while the reality of statistical practice often lies in between. This middle territory is exemplified by “model selection” issues and Frank Harrell’s famous words: “Using the data to guide the data analysis is almost as dangerous as not doing so”. 

The most accomplished confirmatory statistical analyses are conducted in the context of controlled (clinical) trials, where regulations and guidelines are to ensure a fully protocoled and planned statistical analysis. On the other hand, we are now living in the era of “big data” and “data science”, where extreme forms of exploratory data analyses are encouraged with the hope that data quantity prevails over data quality.

While data science is currently in vogue, there is also some perception that “those who ignore statistics are condemned to reinvent it”, as Brad Efron once said. It might be a time to return from the big data paradigm towards more classical approaches and concerns, and to land somewhere between the two extremes of the purely confirmatory and purely exploratory data analyses. 

The XXXIst ROeS statistical conference will be a timely occasion to try to define what this “middle ground” should or could be to best meet the expectations of scientists.

 

Scientific topics

Classical (Confirmatory) Statistics:

  • Biometrical Methods in Agriculture, Forestry and Ecology
  • Causal Inference in Epidemiology
  • Early Phase and Innovative Clinical Trials 
  • Multiple Testing and Adaptive Designs
  • Reproducibility in Biomedical Research 

Statistical Modeling:

  • Bayesian Analysis
  • Evidence Synthesis and Meta-Analysis 
  • Longitudinal and Missing Data
  • Model Selection and Prediction 
  • Survival and Event History Analysis

Data (Exploratory) Science:

  • Challenges and Successes of Big Data
  • Statistical Genomics
  • Machine Learning and Artificial Intelligence
  • Overfitting 
  • Precision Medicine and Biomarker Assessment

 

Scientific programm committee

  • Valentin Rousson (Chair, University of Lausanne)
  • Andrea Berghold (University of Graz)
  • Laura Gosoniu (Nestlé)
  • Georg Heinze (University of Vienna)
  • Dominik Heinzmann (Roche)
  • Leo Held (University of Zurich)
  • Torsten Hothorn (University of Zurich)
  • Zoltan Kutalik (University of Lausanne)
  • Patrick Taffé (University of Lausanne)

 

En savoir plus
Personne de contact: 
                         

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Institut universitaire de médecine sociale et préventive
Route de la Corniche 10, 1010 Lausanne - Switzerland
+41 21 314 72 72 | iumsp@chuv.ch

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