Wavelet-based functional linear mixed models: an application to measurement error-corrected distributed lag models.

ABSTRACT: Frequently, exposure data are measured over time on a grid of discrete values that collectively define a functional observation. In many applications, researchers are interested in using these measurements as covariates to predict a scalar response in a regression setting, with interest focusing on the most biologically relevant time window of exposure. One example is in panel studies of the health effects of particulate matter (PM), where particle levels are measured over time. In such studies, there are many more values of the functional data than observations in the data set so that regularization of the corresponding functional regression coefficient is necessary for estimation. Additional issues in this setting are the possibility of exposure measurement error and the need to incorpor

SUBMITTER: Malloy EJ 

PROVIDER: S-EPMC2883305 | biostudies-literature | 2010 Jul

REPOSITORIES: biostudies-literature