This email address is being protected from spam bots, you need Javascript enabled to view it has been working on the topic of analysis of intensive longitudinal data, which is closely related to functional data analysis in statistical literature. In his work, nonparametric smoothing methods, such as local polynomial regression and penalized regression spline, were used to deal with efficient estimation for various nonparametric regression models and semiparametric regression models. Furthermore, a generalized likelihood ratio type of goodness of fit test is proposed for nonparametric regression models used in intensive longitudinal data analysis. Li is also working on the analysis of ecology momentary assessment (EMA) data, a typical kind of intensive longitudinal data.

This email address is being protected from spam bots, you need Javascript enabled to view it 's research focuses on nonparametric and semiparametric modeling for intensive longitudinal data. Many other statistical modeling strategies have been featured in the new volume, edited by This email address is being protected from spam bots, you need Javascript enabled to view it and This email address is being protected from spam bots, you need Javascript enabled to view it of the Methodology Center and described here.