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   Articles with "regression models" as a keyword



Enhancing the Diagnostic Evaluation of Thyroid Functionality Using Diffuse Reflectance Spectroscopy and Regression Models

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recommendations! Published in 2025 at "Journal of Biophotonics"

DOI: 10.1002/jbio.70010

Abstract: Thyroid dysfunction is a prevalent global health concern that necessitates the development of effective and non‐invasive screening methods to enable early detection. The application of Diffuse Reflectance Spectroscopy (DRS) in conjunction with preprocessing and predictive… read more here.

Keywords: spectroscopy; reflectance spectroscopy; diffuse reflectance; regression models ... See more keywords

Producing chemically accurate atomic Gaussian process regression models by active learning for molecular simulation

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recommendations! Published in 2022 at "Journal of Computational Chemistry"

DOI: 10.1002/jcc.27006

Abstract: Machine learning is becoming increasingly more important in the field of force field development. Never has it been more vital to have chemically accurate machine learning potentials because force fields become more sophisticated and their… read more here.

Keywords: active learning; regression models; chemically accurate; gaussian process ... See more keywords

Logistic regression models of cytokines in differentiating vitreoretinal lymphoma from uveitis

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recommendations! Published in 2022 at "Journal of Clinical Laboratory Analysis"

DOI: 10.1002/jcla.24689

Abstract: Vitreoretinal lymphoma (VRL) can commonly masquerade as chronic idiopathic uveitis due to its nonspecific clinical presentation. Thus, its early diagnosis is difficult. In this study, new logistic regression models were used to classify VRL and… read more here.

Keywords: uveitis; logistic regression; lymphoma; vitreoretinal lymphoma ... See more keywords

A Variance Estimator for Marginal Cox Regression Models Fit to Non‐Nested Multilevel Data

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recommendations! Published in 2025 at "Statistics in Medicine"

DOI: 10.1002/sim.70074

Abstract: In health services research, researchers often use clustered data to estimate the independent association between individual outcomes and cluster‐level covariates after adjusting for individual‐level characteristics. Marginal generalized linear models estimated using generalized estimating equation (GEE)… read more here.

Keywords: regression models; variance estimator; non nested; variance ... See more keywords

Model validation and influence diagnostics for regression models with missing covariates.

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recommendations! Published in 2018 at "Statistics in medicine"

DOI: 10.1002/sim.7584

Abstract: Missing covariate values are prevalent in regression applications. While an array of methods have been developed for estimating parameters in regression models with missing covariate data for a variety of response types, minimal focus has… read more here.

Keywords: regression; validation; regression models; missing covariates ... See more keywords

Group regularization for zero-inflated negative binomial regression models with an application to health care demand in Germany.

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recommendations! Published in 2018 at "Statistics in medicine"

DOI: 10.1002/sim.7804

Abstract: In many biomedical applications, covariates are naturally grouped, with variables in the same group being systematically related or statistically correlated. Under such settings, variable selection must be conducted at both group and individual variable levels.… read more here.

Keywords: regression models; group; zero inflated; group regularization ... See more keywords

Variable selection in semiparametric regression models for longitudinal data with informative observation times.

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recommendations! Published in 2022 at "Statistics in medicine"

DOI: 10.1002/sim.9417

Abstract: A common issue in longitudinal studies is that subjects' visits are irregular and may depend on observed outcome values which is known as longitudinal data with informative observation times (follow-up). Semiparametric regression modeling for this… read more here.

Keywords: regression; informative observation; longitudinal data; semiparametric regression ... See more keywords

Fast estimation of mixed‐effects location‐scale regression models

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recommendations! Published in 2023 at "Statistics in Medicine"

DOI: 10.1002/sim.9679

Abstract: As a result of advances in data collection technology and study design, modern longitudinal datasets can be much larger than they historically have been. Such “intensive" longitudinal datasets are rich enough to allow for detailed… read more here.

Keywords: mixed effects; fast estimation; effects location; regression models ... See more keywords

A Systematic Review and Comparative Study of R Packages for Ordinal Response Regression Models

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recommendations! Published in 2025 at "Wiley Interdisciplinary Reviews: Computational Statistics"

DOI: 10.1002/wics.70025

Abstract: A variable is considered ordinal when it exhibits an ordered categorical scale in which the distance between levels is unknown. Ordinal responses are used in many research fields and, for this reason, require proper statistical… read more here.

Keywords: review; systematic review; regression models; review comparative ... See more keywords

Tests for the linear hypothesis in semi-functional partial linear regression models

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recommendations! Published in 2019 at "Metrika"

DOI: 10.1007/s00184-018-0680-1

Abstract: An empirical likelihood ratio testing method is proposed, in this paper, for semi-functional partial linear regression models. Two empirical likelihood ratio statistics are employed to test the linear hypothesis of parametric components, then we demonstrate… read more here.

Keywords: functional partial; semi functional; linear regression; regression models ... See more keywords

An empirical likelihood method for quantile regression models with censored data

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recommendations! Published in 2020 at "Metrika"

DOI: 10.1007/s00184-020-00775-1

Abstract: An estimation for censored quantile regression models, which is based on an inverse-censoring-probability weighting method, is studied in this paper, and asymptotic distribution of the parameter vector estimator is obtained. Based on the parameter estimation… read more here.

Keywords: quantile regression; regression models; likelihood; method ... See more keywords