Cai Li

Works (7)

Updated: August 6th, 2023 21:16

2021 article

Joint model for survival and multivariate sparse functional data with application to a study of Alzheimer's Disease

Li, C., Xiao, L., & Luo, S. (2021, January 27). Biometrics.

By: C. Li*, L. Xiao n  & S. Luo *

author keywords: EM algorithm; functional mixed model; multivariate longitudinal data; smoothing; survival
MeSH headings : Alzheimer Disease / diagnostic imaging; Databases, Factual; Disease Progression; Humans; Neuroimaging / methods
topics (OpenAlex): Statistical Methods and Inference; Bayesian Methods and Mixture Models; Statistical Methods and Bayesian Inference
TL;DR: A multivariate functional mixed model is proposed to identify the shared progression pattern and outcome‐specific progression patterns of the outcomes, which enables more interpretable modeling of associations between outcomes and AD onset. (via Semantic Scholar)
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Sources: Web Of Science, NC State University Libraries
Added: March 1, 2021

2020 article

Correlation models for monitoring fetal growth

Feng, Y., Xiao, L., Li, C., Chen, S. T., & Ohuma, E. O. (2020, March 23). Statistical Methods in Medical Research.

By: Y. Feng  n, L. Xiao n , C. Li n, S. Chen n & E. Ohuma *

author keywords: Fetal health; longitudinal study; correlation; reference chart
MeSH headings : Female; Femur / diagnostic imaging; Fetal Development; Gestational Age; Humans; Longitudinal Studies; Pregnancy; Ultrasonography, Prenatal
topics (OpenAlex): Birth, Development, and Health; Pregnancy and preeclampsia studies; Statistical Methods in Epidemiology
TL;DR: Using data from the Fetal Growth Longitudinal Study of the INTERGROWTH-21st project, the longitudinal dependence of fetal head circumference, biparietal diameter, occipito-frontal diameter, abdominal circumference, and femur length is modelled using a two-stage approach. (via Semantic Scholar)
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Sources: Web Of Science, NC State University Libraries
Added: April 20, 2020

2020 article

Fast covariance estimation for multivariate sparse functional data

Li, C., Xiao, L., & Luo, S. (2020, January 1). Stat, Vol. 9.

By: C. Li n, L. Xiao n  & S. Luo *

author keywords: bivariate smoothing; covariance function; functional principal component analysis; longitudinal data; multivariate functional data; prediction
topics (OpenAlex): Statistical Methods and Inference; Statistical Methods and Bayesian Inference; Bayesian Methods and Mixture Models
TL;DR: A fast algorithm for selecting the smoothing parameters in covariance smoothing using leave‐one‐subject‐out cross‐validation is derived and applied to an Alzheimer's disease study with multiple longitudinal outcomes. (via Semantic Scholar)
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Sources: Web Of Science, NC State University Libraries
Added: March 1, 2021

2019 article

Conditional Analysis for Mixed Covariates, with Application to Feed Intake of Lactating Sows

Park, S. Y., Li, C., Benavides, S. M. M., Heugten, E., & Staicu, A. M. (2019, July 16). Journal of Probability and Statistics, Vol. 2019.

By: S. Park *, C. Li n, S. Benavides n, E. Heugten  n & A. Staicu n 

topics (OpenAlex): Animal Behavior and Welfare Studies; Genetic and phenotypic traits in livestock; Animal Nutrition and Physiology
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Sources: Web Of Science, NC State University Libraries
Added: August 12, 2019

2017 article

Erratum to: Fast covariance estimation for sparse functional data

Xiao, L., Li, C., Checkley, W., & Crainiceanu, C. (2017, August 23). Statistics and Computing, Vol. 28, pp. 523–523.

By: L. Xiao n , C. Li n, W. Checkley * & C. Crainiceanu *

topics (OpenAlex): Medical Imaging Techniques and Applications
TL;DR: The article, “Fast covariance estimation for sparse functional data”, written by Luo Xiao, Cai Li, William Checkley and Ciprian Crainiceanu, was originally published electronically on the publisher’s Internet portal (currently SpringerLink) on 11 April 2017 without open access. (via Semantic Scholar)
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Sources: Web Of Science, NC State University Libraries
Added: August 6, 2018

2017 article

Fast covariance estimation for sparse functional data

Xiao, L., Li, C., Checkley, W., & Crainiceanu, C. (2017, April 11). Statistics and Computing, Vol. 4, pp. 511–522.

By: L. Xiao n , C. Li n, W. Checkley * & C. Crainiceanu *

author keywords: Bivariate smoothing; FACEs; fPCA
topics (OpenAlex): Statistical Methods and Inference; Bayesian Methods and Mixture Models; Statistical Methods in Epidemiology
TL;DR: The proposed method is a bivariate spline smoother that is designed for covariance smoothing and can be used for sparse functional or longitudinal data and compares favorably against several commonly used methods. (via Semantic Scholar)
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Sources: Web Of Science, ORCID, NC State University Libraries
Added: August 6, 2018

2017 journal article

svt: Singular value thresholding in MATLAB

Journal of Statistical Software, 81(CN2).

By: C. Li & H. Zhou

Source: NC State University Libraries
Added: August 6, 2018

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