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.