General Statistical methods

  • Parametric Methods (ANOVA, regression etc.)
  • Non-Parametrics (rank tests, rank correlation etc.)
  • Categorical data analysis (Odds ratio, logistic regression)
  • Determining of study size, power analysis, sequential studies
  • Bootstrap, permutation tests, Monte-Carlo simulation
  • Time-series analysis of biosignals (Fourier, Powerspectra, Transferfunction)
  • Disease Modeling (Markov chains, trees etc)


Biomarker methods

  • Optimized cutoff search
  • Graphical displays for exploration (e.g. hazard estimation depending on biomarker)
  • Special analysis designs tailored to uncertain biomarkers
  • qRT-PCR scoring
  • Image analysis/scoring of tissue (FISH, IHC)
  • Biological variation, estimation of RCVs


Time-to-Event methods

  • Kaplan-Meier estimation, life-table analysis
  • Cox-proportional hazard model – conditional hazard ratios
  • Frailty analysis, morbidity scores
  • Population Evolution Charts (PEC, cutoff-free association analysis)
  • Non-parametric hazard estimation, hazard dependent on covariates


Multivariate methods

  • Principal Component Analysis, Factor analysis, factor rotation
  • Cluster analysis, canonical correlation
  • Pattern recognition (Discriminant Analysis, Support Vector Machines etc.)
  • Exploratory Analysis e.g. CART
  • Trilinear Decomposition (PARAFAC, CANDECOMP, CP)


Home grown approaches (unpublished)

  • New time-to-event testing facilities (context PEC)
  • Special approaches for estimation of hazard dependencies
  • Test Tuning by Optimal Rank ordering (context rank tests)
  • Special pre-processing in multivariate separation problems (context pattern recognition, discriminant analysis)
  • New algorithmic variants for trilinear modelling
  • Tricks in hierarchical cluster analysis