Project Summary/Abstract The proposed project is in response to PAR-18-857, Diet and Physical Activity Assessment Methodology. We are primarily interested in developing and applying innovative statistical methods for joint modeling of incidence or mortality outcomes and longitudinal physical activity and dietary intake data. Physical activity and diet are important behavioral factors involved in the etiology of many chronic diseases, such as cardio- vascular disease and cancer. We are motivated by longitudinal physical activity measurement issues involved in the Women's Health Initiative (WHI) and the Health, Eating, Activity, and Lifestyle (HEAL) study. The WHI observational study (OS) is a prospective study of health outcomes among 93,676 postmenopausal women enrolled between 1993 and 1998 in 40 U.S. clinical centers. The HEAL study enrolled approximately 1,200 women with early stage breast cancer, diagnosed between 1997-1998, and who have been followed up for more than 15 years. Many nutrient or physical activity measures may have a zero value (or a low de- tectable value) among a group of individuals. Our preliminary simulation results demonstrate that a naive method without taking into account measurement error, or a standard bias correction for mea- surement error without taking into account a subset of individuals with zero values may lead to bias in the effect estimation in regression analysis. Specific aims of this proposal include: (i) To develop and apply methods to adjust for measurement error in joint modeling of binary incidence or mortality outcomes and longitudinal measures of physical activity and dietary intake data, which may be zero among some indi- viduals. (ii) To develop and apply methods to adjust for measurement error in joint modeling of time-to-event survival outcomes and longitudinal measures of physical activity and dietary intake data, which may be zero among some individuals. (iii) To develop and apply methods for time-varying association between time-to- event outcomes and longitudinal measures of physical activity and dietary intake data. The proposed models and methods will be applied to the physical activity and dietary data from both the WHI-OS and the HEAL study. Our new methods will be written in user friendly subroutines via R, which can be used by statisticians, epidemiologists, and other public health professionals. The methods developed in the proposal will have general applications to other studies where longitudinal physical activity and dietary data are available.