Cargando…

Penalized Ordinal Regression Methods for Predicting Stage of Cancer in High-Dimensional Covariate Spaces

The pathological description of the stage of a tumor is an important clinical designation and is considered, like many other forms of biomedical data, an ordinal outcome. Currently, statistical methods for predicting an ordinal outcome using clinical, demographic, and high-dimensional correlated fea...

Descripción completa

Detalles Bibliográficos
Autores principales:	Gentry, Amanda Elswick, Jackson-Cook, Colleen K, Lyon, Debra E, Archer, Kellie J
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Libertas Academica 2015
Materias:	Methodology
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4447150/ https://www.ncbi.nlm.nih.gov/pubmed/26052223 http://dx.doi.org/10.4137/CIN.S17277

Ejemplares similares

ordinalgmifs: An R Package for Ordinal Regression in High-dimensional Data Settings
por: Archer, Kellie J, et al.
Publicado: (2014)

ordinalbayes: Fitting Ordinal Bayesian Regression Models to High-Dimensional Data Using R
por: Archer, Kellie J., et al.
Publicado: (2022)

Obtaining insights from high-dimensional data: sparse principal covariates regression
por: Van Deun, Katrijn, et al.
Publicado: (2018)

Adaptive penalization in high-dimensional regression and classification with external covariates using variational Bayes
por: Velten, Britta, et al.
Publicado: (2019)

Selecting Spatial Scale of Covariates in Regression Models of Environmental Exposures
por: Grant, Lauren P., et al.
Publicado: (2015)

Accounting for grouped predictor variables or pathways in high-dimensional penalized Cox regression models
por: Belhechmi, Shaima, et al.
Publicado: (2020)

Penalized negative binomial models for modeling an overdispersed count outcome with a high-dimensional predictor space: Application predicting micronuclei frequency
por: Lehman, Rebecca R., et al.
Publicado: (2019)

Identifying Molecular Features Associated with Psychoneurological Symptoms in Women with Breast Cancer Using Multivariate Mixed Models
por: Zhou, Qing, et al.
Publicado: (2015)

Identification of gene pairs through penalized regression subject to constraints
por: Shen, Rex, et al.
Publicado: (2017)

Preliminary assessment of three quantitative approaches for estimating time-since-deposition from autofluorescence and morphological profiles of cell populations from forensic biological samples
por: Gentry, Amanda Elswick, et al.
Publicado: (2023)

Gene and pathway identification with L(p )penalized Bayesian logistic regression
por: Liu, Zhenqiu, et al.
Publicado: (2008)

Telomere lengths in women treated for breast cancer show associations with chemotherapy, pain symptoms, and cognitive domain measures: a longitudinal study
por: Alhareeri, Areej A., et al.
Publicado: (2020)

Bayesian variable selection for high-dimensional data with an ordinal response: identifying genes associated with prognostic risk group in acute myeloid leukemia
por: Zhang, Yiran, et al.
Publicado: (2021)

In search of induction and latency periods: Space-time interaction accounting for residential mobility, risk factors and covariates
por: Jacquez, Geoffrey M, et al.
Publicado: (2007)

Differentially penalized regression to predict agronomic traits from metabolites and markers in wheat
por: Ward, Jane, et al.
Publicado: (2015)

Evaluation of logistic regression models and effect of covariates for case–control study in RNA-Seq analysis
por: Choi, Seung Hoan, et al.
Publicado: (2017)

Perceived Stress Levels, Chemotherapy, Radiation Treatment and Tumor Characteristics Are Associated with a Persistent Increased Frequency of Somatic Chromosomal Instability in Women Diagnosed with Breast Cancer: A One Year Longitudinal Study
por: Aboalela, Noran, et al.
Publicado: (2015)

Allowing for mandatory covariates in boosting estimation of sparse high-dimensional survival models
por: Binder, Harald, et al.
Publicado: (2008)

Using ordinal outcomes to construct and select biomarker combinations for single-level prediction
por: Meisner, Allison, et al.
Publicado: (2018)

Genomic-Enabled Prediction of Ordinal Data with Bayesian Logistic Ordinal Regression
por: Montesinos-López, Osval A., et al.
Publicado: (2015)

Generalized Monotone Incremental Forward Stagewise Method for Modeling Count Data: Application Predicting Micronuclei Frequency
por: Makowski, Mateusz, et al.
Publicado: (2015)

Modeling Discrete Survival Time Using Genomic Feature Data
por: Ferber, Kyle, et al.
Publicado: (2015)

Ordinal Logistic Regression in Medical Research
por: Bender, Ralf, et al.
Publicado: (1997)

Application of the common base method to regression and analysis of covariance (ANCOVA) in qPCR experiments and subsequent relative expression calculation
por: Ganger, Michael T., et al.
Publicado: (2020)

Estimating effects of rare haplotypes on failure time using a penalized Cox proportional hazards regression model
por: Souverein, Olga W, et al.
Publicado: (2008)

Elastic SCAD as a novel penalization method for SVM classification tasks in high-dimensional data
por: Becker, Natalia, et al.
Publicado: (2011)

Integrated ordination of miRNA and mRNA expression profiles
por: Diaz, Giacomo, et al.
Publicado: (2015)

Multiple treatment comparisons in a series of anti-malarial trials with an ordinal primary outcome and repeated treatment evaluations
por: Youdom, Solange Whegang, et al.
Publicado: (2012)

Four-Dimensional Gravity on a Covariant Noncommutative Space (II)
por: Manolakos, G., et al.
Publicado: (2021)

Case-control geographic clustering for residential histories accounting for risk factors and covariates
por: Jacquez, Geoffrey M, et al.
Publicado: (2006)

A further critique of the analytic strategy of adjusting for covariates to identify biologic mediation
por: Kaufman, Jay S, et al.
Publicado: (2004)

Restricted maximum likelihood estimation of genetic principal components and smoothed covariance matrices
por: Meyer, Karin, et al.
Publicado: (2005)

Cyclical regression covariates remove the major confounding effect of cyclical developmental gene expression with strain-specific drug response in the malaria parasite Plasmodium falciparum
por: Foster, Gabriel J., et al.
Publicado: (2022)

Covariance regression with random forests
por: Alakus, Cansu, et al.
Publicado: (2023)

Combining acoustic tracking and LiDAR to study bat flight behaviour in three-dimensional space
por: Hermans, Claire, et al.
Publicado: (2023)

Randomized sham controlled trial of cranial microcurrent stimulation for symptoms of depression, anxiety, pain, fatigue and sleep disturbances in women receiving chemotherapy for early-stage breast cancer
por: Lyon, Debra, et al.
Publicado: (2015)

Predicting Progression of Alzheimer’s Disease Using Ordinal Regression
por: Doyle, Orla M., et al.
Publicado: (2014)

Multivariate decoding of brain images using ordinal regression()
por: Doyle, O.M., et al.
Publicado: (2013)

Evaluating Doctor Performance: Ordinal Regression-Based Approach
por: Shi, Yong, et al.
Publicado: (2018)

Distributed Support Vector Ordinal Regression over Networks
por: Liu, Huan, et al.
Publicado: (2022)

Cannot write session to /tmp/vufind_sessions/sess_kmjpvv3j1ubpnajk91obqjd1g1