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.