Chris Wild, Professor of Statistics at the University of Auckland, has earned a high international reputation for his work in several areas of statistics, and the important contribution that he has made to research in other disciplines. One strand of his work is concerned with developing methodology for the design and analysis of medical studies. The methods in his landmark paper “Fitting prospective models to case-control data” have been further developed to enable researchers to use a whole range of new study designs. For example, some of his current work draws on his combined expertise in response-based sampling and frailty modelling to produce efficient methods for handling data from retrospective family studies, a study design that is becoming increasingly important in genetic epidemiology. Other work facilitates designs in which researchers may gather data from large numbers of subjects on inexpensive variables (e.g. demographic variables) but need only obtain data from much smaller subsets of subjects on variables which are either very expensive to obtain (e.g. genetic information) or involve physically invasive procedures. A second strand is his work on nonstandard regression methodology, a subject on which his encyclopaedic book “Nonlinear Regression” with George Seber is the authoritative reference. A third strand of his work with broad international recognition is his research into the philosophy of statistics and modes of statistical thinking; research targeted towards the development in students of the problem-solving thinking patterns of experts.