| A new regression model: modal linear regression W Yao, L Li Scandinavian Journal of Statistics 41 (3), 656-671, 2014 | 157 | 2014 |
| A comparison of residual diagnosis tools for diagnosing regression models for count data C Feng, L Li, A Sadeghpour BMC Medical Research Methodology 20 (1), 1-21, 2020 | 55* | 2020 |
| Sleep duration and sleep disturbances in association with falls among the middle-aged and older adults in China: a population-based nationwide study SK Essien, CX Feng, W Sun, M Farag, L Li, Y Gao BMC geriatrics 18, 1-14, 2018 | 45 | 2018 |
| Deep learning for brain disorder diagnosis based on fMRI images W Yin, L Li, FX Wu Neurocomputing 469, 332-345, 2022 | 41 | 2022 |
| Approximating cross-validatory predictive evaluation in Bayesian latent variable models with integrated IS and WAIC L Li, S Qiu, B Zhang, CX Feng Statistics and Computing 26, 881-897, 2016 | 39 | 2016 |
| Predictive analysis methods for human microbiome data with application to Parkinson’s disease M Dong, L Li, M Chen, A Kusalik, W Xu PLoS One 15 (8), e0237779, 2020 | 20 | 2020 |
| Antimicrobial resistance genetic factor identification from whole-genome sequence data using deep feature selection J Shi, Y Yan, MG Links, L Li, JAR Dillon, M Horsch, A Kusalik BMC bioinformatics 20, 1-14, 2019 | 19 | 2019 |
| Fully Bayesian logistic regression with hyper-LASSO priors for high-dimensional feature selection L Li, W Yao Journal of Statistical Computation and Simulation 88 (14), 2827-2851, 2018 | 19 | 2018 |
| Bayesian hyper-LASSO classification for feature selection with application to endometrial cancer RNA-seq data L Jiang, CMT Greenwood, W Yao, L Li Scientific Reports 10 (1), 1-16, 2020 | 15 | 2020 |
| A method for avoiding bias from feature selection with application to naive bayes classification models L Li, RM Neal, J Zhang | 15 | 2008 |
| Robust descriptive discriminant analysis for repeated measures data TT Sajobi, LM Lix, BM Dansu, W Laverty, L Li Computational Statistics & Data Analysis 56 (9), 2782-2794, 2012 | 13 | 2012 |
| A semi-supervised autoencoder for autism disease diagnosis W Yin, L Li, FX Wu Neurocomputing 483, 140-147, 2022 | 12 | 2022 |
| Estimating cross‐validatory predictive p‐values with integrated importance sampling for disease mapping models L Li, CX Feng, S Qiu Statistics in medicine 36 (14), 2220-2236, 2017 | 9 | 2017 |
| Compressing parameters in Bayesian high-order models with application to logistic sequence models L Li, RM Neal | 9 | 2008 |
| Modeling zero inflation and overdispersion in the length of hospital stay for patients with ischaemic heart disease CX Feng, L Li Advanced Statistical Methods in Data Science, 35-53, 2016 | 8 | 2016 |
| Model diagnostics for censored regression via randomized survival probabilities L Li, T Wu, C Feng Statistics in Medicine, 2021 | 7 | 2021 |
| An online Bayesian mixture labelling method by minimizing deviance of classification probabilities to reference labels W Yao, L Li Journal of statistical computation and simulation 84 (2), 310-323, 2014 | 7 | 2014 |
| A statistical investigation to monitor and understand atmospheric CFC decline with the spatial-longitudinal bent-cable model SA Khan, M Rana, L Li, JA Dubin International Journal of Statistics and Probability 1 (2), 56, 2012 | 7 | 2012 |
| Bias-corrected hierarchical bayesian classification with a selected subset of high-dimensional features L Li Journal of the American Statistical Association 107 (497), 120-134, 2012 | 7 | 2012 |
| Bayesian Classification and Regression with High Dimensional Features L Li arXiv preprint arXiv:0709.2936, 2007 | 6 | 2007 |
Cindy FengDepartment of Community Health and Epidemiology, Dalhousie UniversityVerified email at dal.ca
