Statistical methodology is being applied and developed for longitudinal studies and other studies of aging. The research program focuses on several types of statistical models: 1) longitudinal mixed-effects regression models which consider both within- and between-subject variation in analyzing the repeated measurements for all individuals in the study population, 2) survival analysis for studying risk factors in prospective studies, 3) multiple comparisons for testing group differences in experimental or observational designs, 4) mixture models for describing age changes in distributions of biological markers, and 5) experimental design. Other techniques used include Bayesian, maximum likelihood and numerical computing methods. A major emphasis of the research program is the development of methods which yield cogent yet easily understood results when applied to data. Several models using mixed-effects regression analyses have been developed to study longitudinal data. A piece- wise non-linear mixed-effects regression model was developed to estimate the time at which individuals with prostate cancer developed their tumors during the follow- up period. The model estimates the time when rapid increases in prostate specific antigen (PSA) were first observed beyond the usual background level of PSA change. The Bayesian nature of the mixed-effects model was also used to obtain estimates of a risk factor response that corrected for measurement error bias due to the random variations in the measurements of a risk factor. These shrinkage estimates were then used to provide a """"""""corrected"""""""" value of the risk factor which was used to get a more accurate measure of the strength of the relation between the level of a risk factor and the occurrence of an endpoint such as morbidity or mortality. The research program has extended earlier methods of longitudinal data analysis, introduced novel methods of describing the natural history of aging, and developed new approaches toward the use of longitudinal data in epidemiological and biomedical studies of aging and associated disease states.
