Works Published in 2023

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Displaying works 81 - 100 of 121 in total

Sorted by most recent date added to the index first, which may not be the same as publication date order.

2023 journal article

Scalable Community Extraction of Text Networks for Automated Grouping in Medical Databases

Journal of Data Science.

By: T. Komolafe, A. Fong* & S. Sengupta n

TL;DR: A well-known community extraction method is adapted to develop a scalable algorithm for extracting groups of similar documents in large text databases and it is demonstrated that the groups generated from community extraction are much more accurate than manual tagging by frontline workers. (via Semantic Scholar)
Source: ORCID
Added: May 31, 2023

2023 journal article

Core-periphery structure in networks: A statistical exposition

Statistics Surveys, 17(none), 42–74.

By: E. Yanchenko n & S. Sengupta n

author keywords: Networks; core-periphery structure; meso-scale features
TL;DR: The current research landscape is summarized by reviewing the metrics and models that have been used for quantitative studies on core-periphery structure, and various inferential problems in this context are explored, such as estimation, hypothesis testing, and Bayesian inference. (via Semantic Scholar)
Sources: Web Of Science, NC State University Libraries, Crossref
Added: May 30, 2023

2023 journal article

A PRticle filter algorithm for nonparametric estimation of multivariate mixing distributions

STATISTICS AND COMPUTING, 33(4).

By: V. Dixit n & R. Martin n

author keywords: Importance sampling; Marked point process; Mixture model; Monte Carlo; Predictive recursion
TL;DR: A new strategy is proposed, which is referred to as PRticle filter, wherein the basic PR algorithm is augmented with a filtering mechanism that adaptively reweights an initial set of particles along the updating sequence which are used to obtain Monte Carlo approximations of the normalizing constants. (via Semantic Scholar)
Source: Web Of Science
Added: May 30, 2023

2023 article

Simultaneous modeling of multivariate heterogeneous responses and heteroskedasticity via a two-stage composite likelihood

Ting, B. W. W., Wright, F. A., & Zhou, Y.-H. (2023, May 22). BIOMETRICAL JOURNAL.

By: B. Ting n, F. Wright n & Y. Zhou n

author keywords: heterogeneity; heteroskedasticity; multivariate statistics; precision medicine; prediction
TL;DR: A previous method for multivariate probit estimation is built upon using a two‐stage composite likelihood that exhibits favorable computational time while retaining attractive parameter estimation properties and has the potential to better leverage genomics data and provide interpretable inference for pleiotropy. (via Semantic Scholar)
Sources: ORCID, Web Of Science
Added: May 23, 2023

2023 article

A tiered testing strategy based on in vitro phenotypic and transcriptomic data for selecting representative petroleum UVCBs for toxicity evaluation in vivo

Tsai, H.-H. D., House, J. S., Wright, F. A., Chiu, W. A., & Rusyn, I. (2023, April 20). TOXICOLOGICAL SCIENCES.

author keywords: transcriptomic; petroleum; grouping; dose-response; HTTr; NAMs
MeSH headings : Humans; Transcriptome; Petroleum / toxicity; Endothelial Cells; Gene Expression Profiling; Cell Line
TL;DR: This study found that two cell types-iPSC-derived-hepatocytes and -cardiomyocytes-contributed the most informative and protective PODs and may be used to inform selection of representative petroleum UVCBs for further toxicity evaluation in vivo. (via Semantic Scholar)
UN Sustainable Development Goal Categories
Source: Web Of Science
Added: May 22, 2023

2023 article

Targeted optimal treatment regime learning using summary statistics

Chu, J., Lu, W., & Yang, S. (2023, March 15). BIOMETRIKA, Vol. 3.

By: J. Chu n, W. Lu n & S. Yang n

author keywords: Covariate shift; Double robustness; Empirical likelihood; Entropy balancing; Multisource policy learning
TL;DR: This work proposes a calibrated augmented inverse probability weighted estimator of the value function for the target population and estimates an optimal treatment regime by maximizing this estimator within a class of pre-specified regimes and develops a weighting framework that tailors a treatment regime for a given target population by leveraging the available summary statistics. (via Semantic Scholar)
UN Sustainable Development Goal Categories
16. Peace, Justice and Strong Institutions (OpenAlex)
Sources: Web Of Science, NC State University Libraries
Added: May 22, 2023

2023 journal article

Genetic Modifiers of Cystic Fibrosis Lung Disease Severity

AMERICAN JOURNAL OF RESPIRATORY AND CRITICAL CARE MEDICINE, 207(10), 1324–1333.

By: Y. Zhou*, P. Gallins*, R. Pace*, H. Dang*, M. Aksit, E. Blue*, K. Buckingham*, J. Collaco ...

author keywords: cystic fibrosis; whole-genome sequencing; lung disease severity; GWAS/TWAS; pathway analyses
MeSH headings : Humans; Cystic Fibrosis / genetics; Genome-Wide Association Study / methods; Cystic Fibrosis Transmembrane Conductance Regulator / genetics; Patient Acuity; Lung; Microtubule-Associated Proteins / genetics
TL;DR: This pre- modulator genomic, transcriptomic, and pathway association study of 7,840 pwCF will facilitate mechanistic and post-modulator genetic studies and, development of novel therapeutics for CF lung disease. (via Semantic Scholar)
UN Sustainable Development Goal Categories
3. Good Health and Well-being (Web of Science; OpenAlex)
Sources: Web Of Science, ORCID, NC State University Libraries
Added: May 16, 2023

2023 journal article

Deep spectral Q-learning with application to mobile health

STAT, 12(1).

By: Y. Gao n, C. Shi* & R. Song n

author keywords: dynamic treatment regimes; mixed frequency data; principal component analysis; reinforcement learning
TL;DR: A deep spectral Q‐learning algorithm is proposed, which integrates principal component analysis (PCA) with deep Q‐learning to handle the mixed frequency data and proves that the mean return under the estimated optimal policy converges to that under the optimal one and establishes its rate of convergence. (via Semantic Scholar)
UN Sustainable Development Goal Categories
Sources: Web Of Science, NC State University Libraries
Added: May 15, 2023

2023 journal article

Posterior contraction and testing for multivariate isotonic regression

ELECTRONIC JOURNAL OF STATISTICS, 17(1), 798–822.

author keywords: Multivariate isotonic regression; contraction rate; Bayesian tests for multivariate monotonicity
UN Sustainable Development Goal Categories
4. Quality Education (Web of Science)
Source: Web Of Science
Added: May 15, 2023

2023 journal article

Automated Error Labeling in Radiation Oncology via Statistical Natural Language Processing

DIAGNOSTICS, 13(7).

By: I. Ganguly n, G. Buhrman*, E. Kline, S. Mun* & S. Sengupta n

author keywords: patient safety; medical errors; neural networks; text classification; statistical modeling
TL;DR: Text-classification models developed with clinical data from a full service radiation oncology center (test center) that can predict the broad level and first level category of an error given a free-text description of the error are demonstrated. (via Semantic Scholar)
UN Sustainable Development Goal Categories
4. Quality Education (OpenAlex)
Sources: Web Of Science, ORCID, NC State University Libraries
Added: May 9, 2023

2023 article

Distributed Inference for Spatial Extremes Modeling in High Dimensions

Hector, E. C., & Reich, B. J. (2023, April 12). JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, Vol. 4.

By: E. Hector n & B. Reich n

author keywords: Bias-variance tradeoff; Brown-Resnick process; Divide-and-conquer; Scalable computing
TL;DR: A spatial partitioning approach based on local modeling of subsets of the spatial domain that delivers computationally and statistically efficient inference and leads to a surprising reduction in bias of parameter estimates over a full data approach is proposed. (via Semantic Scholar)
UN Sustainable Development Goal Categories
13. Climate Action (Web of Science)
Sources: Web Of Science, NC State University Libraries, ORCID
Added: May 9, 2023

2023 article

D- and A-Optimal Screening Designs

Stallrich, J., Allen-Moyer, K., & Jones, B. (2023, April 7). TECHNOMETRICS.

By: J. Stallrich n, K. Allen-Moyer n & B. Jones

author keywords: Bayesian optimal design; Blocking; Coordinate exchange algorithm; Factorial experiments; Minimum aliasing
UN Sustainable Development Goal Categories
2. Zero Hunger (Web of Science)
Source: Web Of Science
Added: May 9, 2023

2023 article

On Learning and Testing of Counterfactual Fairness through Data Preprocessing

Chen, H., Lu, W., Song, R., & Ghosh, P. (2023, April 12). JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, Vol. 4.

author keywords: Causal inference; Conditional independence test; Fairness learning; Machine learning ethics; Structural causal model
TL;DR: The Fair Learning through dAta Preprocessing (FLAP) algorithm is developed to learn counterfactually fair decisions from biased training data and formalize the conditions where different data preprocessing procedures should be used to guarantee counterfactual fairness. (via Semantic Scholar)
Sources: Web Of Science, NC State University Libraries
Added: May 1, 2023

2023 journal article

Second-Generation Functional Data

ANNUAL REVIEW OF STATISTICS AND ITS APPLICATION, 10, 547–572.

By: S. Koner* & A. Staicu n

author keywords: functional principal component analysis; spatial functional data; longitudinal functional data; functional time series; multivariate functional data
Sources: Web Of Science, NC State University Libraries
Added: April 24, 2023

2023 article

Soft calibration for selection bias problems under mixed-effects models

Gao, C., Yang, S., & Kim, J. K. (2023, March 2). BIOMETRIKA, Vol. 3.

By: C. Gao n, S. Yang n & J. Kim*

author keywords: Inverse propensity score weighting; Latent ignorability; Penalized optimization; Restricted maximum likelihood estimation
TL;DR: A soft calibration scheme, in which the outcome and the selection indicator follow mixed-effects models, which has an intrinsic connection with best linear unbiased prediction, which results in a more efficient estimation compared to hard calibration. (via Semantic Scholar)
UN Sustainable Development Goal Categories
16. Peace, Justice and Strong Institutions (OpenAlex)
Sources: Web Of Science, NC State University Libraries, ORCID
Added: April 19, 2023

2023 article

Elastic integrative analysis of randomised trial and real-world data for treatment heterogeneity estimation

Yang, S., Gao, C., Zeng, D., & Wang, X. (2023, April 6). JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY, Vol. 4.

author keywords: counterfactual outcome; least favourable confidence interval; non-regularity; precision medicine; pre-test estimator; semiparametric efficiency
TL;DR: A test-based elastic integrative analysis of the randomised trial and real-world data to estimate treatment effect heterogeneity with a vector of known effect modifiers with a good finite-sample coverage property is proposed. (via Semantic Scholar)
Sources: Web Of Science, NC State University Libraries, ORCID
Added: April 19, 2023

2023 article

Statistical inference for streamed longitudinal data

Luo, L., Wang, J., & Hector, E. C. (2023, February 20). BIOMETRIKA, Vol. 2.

author keywords: Generalized method of moments; Online learning; Quadratic inference function; Scalable computing; Serial dependence
UN Sustainable Development Goal Categories
2. Zero Hunger (OpenAlex)
Sources: Web Of Science, NC State University Libraries, ORCID
Added: April 17, 2023

2023 journal article

Tuning parameter selection for penalized estimation via R2

COMPUTATIONAL STATISTICS & DATA ANALYSIS, 183.

By: J. Holter n & J. Stallrich n

author keywords: Cross validation; Model; variable selection; Functional data; Relaxed lasso
TL;DR: A simple, yet powerful cross-validation strategy based on maximizing squared correlations between the observed and predicted values, rather than minimizing squared error loss for the purposes of support recovery is proposed. (via Semantic Scholar)
Source: Web Of Science
Added: April 11, 2023

2023 journal article

Robust Low-Rank Tensor Decomposition with the L 2 Criterion

Technometrics.

TL;DR: A robust Tucker decomposition estimator based on the L2 criterion, called the Tucker- is presented, which has empirically stronger recovery performance in more challenging high-rank scenarios compared with existing alternatives. (via Semantic Scholar)
Source: ORCID
Added: April 11, 2023

2023 article

Soft Functionally Gradient Materials and Structures - Natural and Manmade: A Review

Pragya, A., & Ghosh, T. K. (2023, October 22). ADVANCED MATERIALS, Vol. 10.

By: A. Pragya n & T. Ghosh n

author keywords: compositional gradients; soft functionally gradient materials; structural gradients
Sources: ORCID, Web Of Science, NC State University Libraries
Added: April 9, 2023

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