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
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.
PROPOSED COMMERCIAL APPLICATIONS:
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.
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