High-dimensional inference and complex data workshop

Presentations

• Luigi Auguliaro, A differential geometric approach to identify important variables in GLMs when p >> n
• Keith Baggerly, The importance of reproducibility in high-throughput biology: a case study
  Paper: Deriving chemosensitivity from cell lines: Forensic Bioinformatics and reproducible research in high-throughput Biology
• Peter Diggle, Geostatistical inference under preferential sampling
• Paul Eilers, Efficient computation with data grids
• Siem Heisterkamp, Pharmacogenetic analysis in clinical trials using Elastic Net
• Hans van Houwelingen, Fitting survival models with p>>n predictors: beyond proportional hazards
• Goeran Kauermann, Penalized spline smoothing, mixed models and Bayesian statistics - three successful players in a liaison
• John Nerbonne, Analysing language variation: high dimensional, geographically structured data
• Stephen Senn, 'There's less to this than meets the eye' — a sceptical look at personalised medicine
• Tom Snijders, Statistical modelling of social network dynamics
• Simon Wood, Generalized additive models.
  Part 1: GAMs - semi-parametric GLMs.
  Part 2: A toolbox of smooths.
  Part 3: Checking, Selecting & Predicting with GAMs.