Dr. Province has made most of his methodological contributions to population genetics and genetic epidemiology. He helped develop a longitudinal, growth curve model of treatment effect using an extended baseline period via the E-M algorithm; created a Poisson-Process model for segregation analysis; developed a temporal trend methodology for assessing age effects in familial resemblance; extended that to the resolution of polygenic versus cultural inheritance; and finally to a repeated measures model for the assessment of developmental genetic effects in longitudinal data. He has also developed a generalized model and program for performing combined path, segregation and variance-components linkage analysis using a model building syntax (SEGPATH). This approach has already shown itself to be very flexible and useful in quickly implementing new state-of-the art genetic models, including multilocus, multiphenotype models for complex traits. He has helped develop frailty models for age-at-onset phenotypes, regression tree/recursive partitioning linkage analysis methods, and meta-analysis linkage procedures. Dr. Province has also developed a novel Sequential Multiple Decision Procedure for linkage analysis to simultaneously identify all promising areas in a genome scan while controlling for overall type I and type II error rates.