Specialising in data management, descriptive to advanced statistical data analysis, multivariate regression, model validation and fit, Bayesian statistics, time series forecasting and aberration analysis as well as geostatistical spatial modelling and kriging. Offering statistics help for companies and academic staff, students or institutions (e.g. analysis and support for research, dissertations, thesis, publications). This statistical consulting company is a registered close corporation with the support of a university post graduate statistician who has published in high impact journals such as the Lancet (see Qualifications). Advanced user of the following software packages: Microsoft SQL Server, Microsoft Excel,Stata, R, MapInfo Professional (GIS), WinBUGS.
Example: Bayesian spatial kriging
Example: time series forecasting
Example: time series aberration detection
Areas of expertise
Descriptive and advanced statistics
Classical and Bayesian statistical data analysis
Parametric and non-parametric statistics
Correlation matrices and analysis
Time series and forecasting modelling and analysis of mortality or financial data (autoregressive, moving averages etc), confidence intervals, credibility intervals etc
Simple to advanced aberration (threshold) detection methods for mass gathering events such as the 2010 FIFA Soccer World Cup e.g. statistician developed and implemented mortality spatial-temporal aberration detection system in Sweden
Analytical epidemiology analysis e.g. case-control or cohort study, one to multiple sample comparison tests such as t-test, Mann-Whitney, etc
Direct and indirect standardization for comparison of rates
Spatial-temporal analysis using clustering analysis and Bayesian kriging using areal and geostatistical techniques
GIS e.g. calculating network and straight-line distance, extracting information from digital elevation models (DEM) etc
Principle Component Analysis (PCA) and Multiple Correspondence Analysis (MCA)
Factor analysis
Mortality and survival regression modelling such as event history, non-parametric Cox, parametric Weibull etc, risk factor analysis (e.g. gender or sex etc)
Other multivariate regression modelling – linear, ordinal (Likert scale data), nominal, logistic, Poisson, negative binomial etc
Model diagnostics and checking of assumptions, fit and validation
Get simple to advanced statistical data analysis support to suit all your needs whether academic (dissertation / thesis help) or professional / corporate.
Please see link for contact details of the statistician.
