Dr. Grace Y. Yi

Department of Statistics and Actuarial Science

University of Waterloo

Title: "Analysis of Longitudinal Data with Measurement Error in Covariates"

Longitudinal data analysis has attracted considerable research interest. Various methods,
such as likelihood, imputation, and weighted estimating equations approaches, have been
developed to accommodate distint features of longitudinal studies. Often,efforts are mainly
devoted to address correlation among repeated measurements and missingness of longitudinal
data. However, covariate measurement error is also typical for longitudinal data. In practice
it often happens that some collected data are subject to measurement error. Sometimes covariates
may be difficult to observe precisely due to physical location or cost. Sometimes it is
impossible to measure covariates accurately due to their nature. In other situations, a covariate
may represent an average of a certain quantity over time, and any practical way of measuring such
a quantity necessarily features measurement error. When carrying out statistical inference in such
settings, it is important to account for the effects of mismeasured covariates; otherwise,
erroneous or even misleading results may be produced. In this talk, I will briefly review
measurement error models in various contexts, and then focus the discussion on some marginal
methods for analyzing longitudinal data with covariate measurement error as well as missing