Home Research Areas Intensive Longitudinal Data Bibliography

Fan, J. & Li, R., (2004). New estimation and model selection procedures for semiparametric modeling in longitudinal data analysis. Journal of American Statistical Association, 99, 710-723.

Li, R. & Chow, M., (2005). Evaluation of reproducibility for paired functional data. Journal of Multivariate Analysis, 93, 81-101.

Qu, A.P. & Li, R., (2006). Nonparametric modeling and inference function for longitudinal data. Biometrics, 62, 379-391.

Li, R., Root, R. & Shiffman, S., (2006). A local linear estimation procedure for functional multilevel modeling. In Models for Intensively Longitudinal Data, (T. Walls and J. Schafer, Eds.) 63-83, Oxford University Press.

Li, R. & Nie, L., (2007). A new estimation procedure for partially nonlinear model via a mixed effects approach. Canadian Journal of Statistics, 35, 399-411.

Fan, J., Huang, T. & Li, R., (2007). Analysis of longitudinal data with semiparametric estimation of covariance function. Journal of American Statistical Association, 102, 632-641.

Dziak, J. & Li, R., (2007). An overview on variable selection for longitudinal data. Quantitative Medical Data Analysis using Mathematical Tools and Statistical Techniques, (D. Hong and Y. Shyr, eds). 3-24. World Sciences Publisher, Singapore.

Li, R. & Liang, H., (2008). Variable selection in semiparametric regression modeling. Annals of Statistics, 36, 261-286.

Li, R. & Nie, L., (2008). Efficient statistical inference procedures for partially nonlinear models and their applications. Biometrics, 904-911.

Liang, H. & Li, R., (2009). Variable selection for partially linear models with measurement Errors. Journal of American Statistical Association, 104, 234-248.

Ma, Y. & Li, R. Variable selection in measurement error models. Tentatively accepted by Bernoulli.