Refereed Journal Papers
*Master student; **PhD student; __Corresponding author
Chen, L.-P., Wu, J.-C.**, and Yi, G. Y. (2025+). Semiparametric estimation for error-prone partially linear single-index models. Journal of Computational and Graphical Statistics. To appear.
Chen, L.-P. (2025+). Variable selection via penalized ridge regression with error prone variables. Annals of the Institute of Statistical Mathematics, 1-37. To appear.
Chen, L.-P. and Huang, W.-H. (2025). Nonparametric profile monitoring with error-prone auxiliary variables. Computers & Industrial Engineering, 209, 111510.
Wu, J.-C.** and Chen, L.-P. (2025). Transfer learning for error-contaminated Poisson regression models. Statistics in Medicine, 44: e70163.
Chen, L.-P. and Hsu, W.-H.* (2025). CHEMIST: An R package for causal inference with high-dimensional error-prone covariates and misclassified treatments. Japanese Journal of Statistics and Data Science, 8, 349-365. (Invited submission for the special issue: Recent Advances in Biostatistics).
Chen, L.-P. (2025). Analysis of receiver operating characteristic curves for cure survival data and mismeasured biomarkers. Mathematics, 13, 424. (special issue: Statistical Analysis and Data Science for Modern Complex Data)
Chen, L.-P. (2025). Nonparametric estimation for propensity scores with misclassified treatments. Statistics in Medicine, 44: e10306.
Chen, L.-P. and Tsao, H.-S.* (2024). GUEST: An R package for handling estimation of graphical structure and multi-classification for error-prone gene expression data. Bioinformatics, 40(12), btae731.
Chen, L.-P. and Lin, C.-K.** (2024). EATME: An R package for EWMA control charts with adjustments of measurement error. PLOS ONE, 19(10): e0308828.
Chen, L.-P. and Yi, G. Y. (2024). AteMeVs: An R package for estimation of the average treatment effects with measurement error and variable selection for confounders. PLOS ONE, 19(9): e0296951.
Chen, L.-P. (2024). Accelerated failure time models with error-prone response and nonlinear covariates. Statistics and Computing, 34:183.
Chen, L.-P. and Huang, H.-T.* (2024). AFFECT: An R package for accelerated functional failure time model with error-contaminated survival times and applications to gene expression data. BMC Bioinformatics, 25:265.
Chen, L.-P. (2024). Estimation of graphical models: An overview of selected topics. International Statistical Review, 92, 194-245.
Chen, L.-P. (2024). Feature screening via concordance indices for left-truncated and right-censored survival data. Journal of Statistical Planning and Inference, 232, 106153.
Chen, L.-P. (2024). Variable selection and estimation for misclassified binary responses and multivariate error-prone predictors. Journal of Computational and Graphical Statistics, 33, 407-420.
Chen, L.-P. and Yi, G. Y. (2024). Unbiased boosting estimation for censored survival data. Statistica Sinica, 34, 439-458.
Chen, L.-P. and Qiu, B.* (2023). SIMEXBoost: An R package for analysis of high-dimensional error-prone data based on boosting method. The R Journal, 15, 5-20.
Chen, L.-P. and Qiu, B.* (2023). Analysis of length-biased and partly interval-censored survival data with mismeasured covariates. Biometrics, 79, 3929-3940.
Chen, L.-P. (2023). A note of feature screening via rank-based coefficient of correlation. Biometrical Journal, 65, 2100373.
Zhang, Q., Yi, G. Y., Chen, L.-P., and He, W. (2023). Sentiment analysis and causal learning of COVID-19 Tweets prior to the roll out of vaccines. PLOS ONE, 18(2): e0277878.
Yi, G. Y. and Chen, L.-P. (2023). Estimation of the average treatment effect with variable selection and measurement error simultaneously addressed for potential confounders. Statistical Methods in Medical Research, 32, 691-711.
Chen, L.-P. (2023). De-noising boosting methods for variable selection and estimation subject to error-prone variables. Statistics and Computing, 33:38.
Chen, L.-P. and Yang, S.-F. (2023). A new p-chart with measurement error correction. Quality and Reliability Engineering International, 39, 81-98.
Chen, L.-P. (2022). BOOME: A Python package for handling misclassified disease and ultrahigh-dimensional error-prone gene expression data. PLOS ONE, 17(10): e0276664.
Chen, L.-P. (2022). Classification and prediction for multi-cancer data with ultrahigh-dimensional gene expressions. PLOS ONE, 17(9): e0274440.
Chen, L.-P. and Yi, G. Y. (2022). De-noising analysis of noisy data with graphical models. Electronic Journal of Statistics, 16, 3861-3909.
Chen, L.-P. (2022). Network-based discriminant analysis for multiclassification. Journal of Classification, 39, 410-431.
Chen, L.-P. and Yi, G. Y. (2022). Sufficient dimension reduction for survival data analysis with error-prone variables. Electronic Journal of Statistics, 16, 2082-2123.
Chen, L.-P. and Yi, G. Y. (2021). Analysis of noisy survival data with graphical proportional hazards measurement error models. Biometrics, 77, 956–969.
Chen, L.-P. and Yi, G. Y. (2021). Semiparametric methods for left-truncated and right-censored survival data with covariate measurement error. Annals of the Institute of Statistical Mathematics, 73, 481–517.
Chen, L.-P., Zhang, Q., Yi, G. Y., and He, W. (2021). Model-based forecasting for Canadian COVID-19 data. PLOS ONE, 16(1): e0244536.
Chen, L.-P. and Yi, G. Y. (2020). Model selection and model averaging for analysis of truncated and censored data with measurement error. Electronic Journal of Statistics, 14, 4054-4109.
Chen, L.-P., Yi, G. Y., Zhang, Q., and He, W. (2019). Multiclass analysis and prediction with network structured covariates. Journal of Statistical Distributions and Applications (invited submission), 6:6.
Book Review Papers
Chen, L.-P. (2023). Statistical Inference and Machine Learning for Big Data by Mayer Alvo. Biometrics, 79, 4013-4013.
Chen, L.-P. (2023). Fundamentals of High-Dimensional Statistics: With Exercises and R Labs by Johannes Lederer. Biometrics, 79, 2772-2773.
Chen, L.-P. (2023). Statistical Inference and Machine Learning for Big Data by Mayer Alvo. Biometrics. In Production.
Chen, L.-P.(2022). Handbook of Measurement Error Models by Grace Y. Yi, Aurore Delaigle, and Paul Gustafson. Biometrics, 78, 1269-1270.
Chen, L.-P. (2022). Introduction to Data Science: Data Analysis and Prediction Algorithms with R by Rafael A. Irizarry. Journal of the Royal Statistical Society, Series A, 185, 733-734.
Chen, L.-P. (2022). Bayesian Analysis of Infectious Diseases: COVID-19 and Beyond by Lyle D. Broemeling. Journal of the Royal Statistical Society, Series A, 185, 729-730.
Chen, L.-P. (2022). Handbook of Meta-Analysis by Christopher H. Schmid, Theo Stijnen, and Ian White. Biometrics, 78, 819-820.
Twitter recommend: https://twitter.com/RobCalver5/status/1548983528221810689
Chen, L.-P. (2021). The ESD Control Program Handbook by Jeremy M. Smallwood. Technometrics, 64, 148-149.
Chen, L.-P. (2021). Statistical Foundations of Data Science by Jianqing Fan, Runze Li, Cun-Hui Zhang, and Hui Zou. Biometrics, 77, 1132-1135.
Chen, L.-P. (2021). Practical Statistics for Data Scientists: 50+ Essential Concepts Using R and Python by Peter Bruce, Andrew Bruce, and Peter Gedeck. Technometrics, 62, 272-273.
Conference Papers/Book Proceedings
Chen, L.-P., Wu, J.-C.** and Tsao, H.-S.* (2025+). Ultrahigh-dimensional discriminant analysis and its application to gene expression data. Big Data Analysis, Biostatistics and Bioinformatics (ICSA Book Series). Springer, Cham. In production.
Chen, L.-P. and Yi, G. Y. (2022). Robust feature screening for ultrahigh-dimensional censored data subject to measurement error. In: He, W., Wang, L., Chen, J., Lin, C.D. (eds) Advances and Innovations in Statistics and Data Science (ICSA Book Series in Statistics). Springer, Cham, 23-53.
He, W., Yi, G. Y., and Chen, L.-P. (2019). Support vector machine with graphical network structures in features. Proceedings, Machine Learning and Data Mining in Pattern Recognition, 15th International Conference on Machine Learning and Data Mining, MLDM 2019, vol.II, 557-570.