Research Interests
Geospatial Health Data Modeling
Identify risk factors and quantify disease risk that explains the variation in space and time
Research in Biostatistics education
Teaching and learning of Biostatistics. Methods of Biostatistics education incorporating technology tools and assessment integrated learning.
Modelling non-linear relationships
Application of generalised additive models, fractional polynomials and splines. Pooling of individual participant data with non-linear patterns from different studies.
Predictive modeling
Using dynamic prediction, pattern recognition, data mining, machine learning, artificial intelligence, or knowledge discovery to develop a statistical tool or models that generates a reliable prediction.