Event history analysis methods are widely used in medical research: for example in clinical trials, in pharmacological studies, in studying the effects of ionizing radiation., in screening for breast and colorectal cancer, and in the study of sexually transmitted diseases. Recently there has been considerable interest in the biostatistics literature regarding the use of splines in estimating the log-hazard function. We propose to incorporate recent and ongoing advances in this area into HARE, a product utilizing adaptive polynomial spline technology for the analysis of event history data. When the observed failure times are generated by an unknown mechanism, interest often lies in estimating a hazard, survival, or density function. In HARE these functions are estimated by means of polynomial splines and their selected tensor products in univariate and multivariate survival models with covariates. MARS-like methods are used to adaptively select the spline basis functions. HARE will also compute standard test statistics, provide an easy-to-use graphical user interface with extensive guidance capabilities, and comprehensively graphically display the computed estimates and diagnostics.
Event history analysis, especially survival analysis, is one of the most heavily used statistical methods. The HARE module adds an exciting new dimension to event history analysis. MathSoft intends to target the biomedical and reliability engineering markets with HARE. Each of these markets represents tens of thousands of potential users. It is difficult to envision a commercial situation in the statistical software arena that is more likely to succeed.
