Statistical Analysis

Analysing data can be a complex process. New methods are being continually developed, building on the strengths and successes of established approaches.

We have particular expertise in:

  • regression and generalized linear models (GLMs)
  • multilevel models
  • multivariate analysis
  • Bayesian statistics
  • longitudinal data analysis
  • structural equation modelling (SEM)

Some recommended resources

  • Albert, J. 2007. Bayesian Computation with R. 2nd Edition. Springer.
  • Everitt, B. and Hothorn, T. 2011. An Introduction to Applied Multivariate Analysis with R. Springer.
  • Fitzmaurice, G.M. Laird, N.M. and Ware, J.H. 2011. Applied Longitudinal Analysis. Wiley: New York.
  • Fox, J. and Weisberg, S. 2010. An R Companion to Applied Regression. SAGE.
  • Gelman, A. and Hill, J. 2007. Data Analysis using Regression and Hierarchical/Multilevel Modeling. Cambridge.
  • Twisk, J.W.R. 2003. Applied Longitudinal Data Analysis for Epidemiology. Cambridge.