Quantitative Methods

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CBG has extensive expertise with most forms of biostatistical analysis. We can provide both advice - including suggestions as to appropriate statistical analyses and power calculations, and provide the analyses themselves. 

We can provide all standard epidemiological analyses from simple 2x2 and more complicated tabular analyses, through regression models, including logistic and Poisson regressions, to analyses of censored data, proportional hazards models and complex stratified designs. We have experience with random effects models and multilevel modeling. 

Multilevel models are a particularly powerful and appropriate method for analysing unbalanced clustered data, including survey data. For data collected in hierarchical health structures - patients within wards within hospitals, or doctors within practices within PHOs - multilevel models usually provide the best analytic framework. 

CBG is also experienced with the various ANOVA analyses, most forms of regression analysis (and model adequacy testing), and with data reduction techniques such as cluster analysis, factor analysis, and principal components analysis. CBG can handle non-parametric data - from simple rank statistics through to complicated categorical modelling. 

Finally, CBG has experienced analysts available to work on time series data, econometric modelling and data-mining. Whatever your quantitative data analysis needs, CBG Health Research has experienced personnel and state-of-the-art software available to help.