Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Regression Toward the Mean01:52

Regression Toward the Mean

7.2K
Regression toward the mean (“RTM”) is a phenomenon in which extremely high or low values—for example, and individual’s blood pressure at a particular moment—appear closer to a group’s average upon remeasuring. Although this statistical peculiarity is the result of random error and chance, it has been problematic across various medical, scientific, financial and psychological applications. In particular, RTM, if not taken into account, can interfere when...
7.2K
Multiple Regression01:25

Multiple Regression

4.0K
Multiple regression assesses a linear relationship between one response or dependent variable and two or more independent variables. It has many practical applications.
Farmers can use multiple regression to determine the crop yield based on more than one factor, such as water availability, fertilizer, soil properties, etc. Here, the crop yield is the response or dependent variable as it depends on the other independent variables. The analysis requires the construction of a scatter plot...
4.0K
Correlation and Regression00:53

Correlation and Regression

3.5K
In statistics, correlation describes the degree of association between two variables. In the subfield of linear regression, correlation is mathematically expressed by the correlation coefficient, which describes the strength and direction of the relationship between two variables. The coefficient is symbolically represented by 'r' and ranges from -1 to +1. A positive value indicates a positive correlation where the two variables move in the same direction. A negative value suggests a...
3.5K
Regression Analysis01:11

Regression Analysis

8.5K
Regression analysis is a statistical tool that describes a mathematical relationship between a dependent variable and one or more independent variables.
In regression analysis, a regression equation is determined based on the line of best fit– a line that best fits the data points plotted in a graph. This line is also called the regression line. The algebraic equation for the regression line is called the regression equation. It is represented as:
8.5K
Microsoft Excel: Regression Analysis01:18

Microsoft Excel: Regression Analysis

1.6K
Regression analysis in Microsoft Excel is a powerful statistical method for examining the relationship between a dependent variable and one or more independent variables. It's used extensively in fields such as economics, biology, and business to predict outcomes, understand relationships, and make data-driven decisions. The most common type is linear regression, which attempts to fit a straight line through the data points to model the relationship between variables.
To perform regression...
1.6K
Natural Selection and Adaptation01:15

Natural Selection and Adaptation

1.5K
Natural selection, a fundamental concept in evolutionary biology, is the mechanism by which evolution is driven, favoring organisms that are best adapted to their environments. This process enhances their chances of survival and reproduction. Adaptation, a key outcome of this process, involves genetic modifications that optimize an organism's functionality under specific environmental challenges, such as extreme cold or thinner air at high altitudes.
Beyond physical adaptations,...
1.5K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Chemically Programmable Underwater Sound-Absorbing Metamaterial via MXene Self-Assembly.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)·2026
Same author

Visualizing the Hidden Atomic Pathways of Iron Oxidation.

Journal of the American Chemical Society·2026
Same author

Structure-optimized 4-trifluoromethylquinoline derivatives: Dual enhancement of SGK1 inhibition and anti-prostate cancer efficacy.

Bioorganic chemistry·2026
Same author

Attenuated FTO induces necroptosis of alveolar epithelium via the m<sup>6</sup>A/CYP1B1/ROS/MLKL axis to promote the aggravation of pulmonary emphysema.

Redox biology·2026
Same author

CRI-CCTG-0003/IND.240 an immunotherapy platform study in platinum-resistant high grade serous ovarian cancer (IPROC): Sub-studies A and B: Durvalumab (D) + mecbotamab vedotin (BA3011) or ozuriftamab vedotin (BA3021).

Cancer treatment and research communications·2026
Same author

Interstitial C/N Doping Stabilizes Pd@Pt Core-Shell Electrocatalysts by Atomic-Scale Interfacial Anchoring and Metal Dissolution Suppression.

Angewandte Chemie (International ed. in English)·2026
Same journal

Regression analysis of misclassified current status data with potentially unknown test accuracy.

Statistical methods in medical research·2026
Same journal

Bayesian multivariate linear mixed-effects models with varied association structures.

Statistical methods in medical research·2026
Same journal

Inference about the ratio of age-standardized rates between two overlapping populations.

Statistical methods in medical research·2026
Same journal

A robust neural network with random effects for subject-specific prediction of clustered count data.

Statistical methods in medical research·2026
Same journal

A comparison of methods for designing hybrid type 2 cluster-randomized trials with continuous effectiveness and implementation endpoints.

Statistical methods in medical research·2026
Same journal

Joint analysis of longitudinal and recurrent event data: A functional regression approach with autoregressive frailty.

Statistical methods in medical research·2026
See all related articles

Related Experiment Video

Updated: Feb 14, 2026

Establishing a Competing Risk Regression Nomogram Model for Survival Data
04:57

Establishing a Competing Risk Regression Nomogram Model for Survival Data

Published on: October 23, 2020

10.9K

Efficient robust doubly adaptive regularized regression with applications.

Rohana J Karunamuni1, Linglong Kong1, Wei Tu1

  • 1Department of Mathematical and Statistical Sciences, University of Alberta, Alberta, Canada.

Statistical Methods in Medical Research
|February 17, 2018
PubMed
Summary
This summary is machine-generated.

This study introduces a robust penalized regression method for linear models. It achieves efficient variable selection and estimation, even with outliers present, by using adaptive weights.

Keywords:
Regularized regressionefficiencyrobustnessvariable selection

More Related Videos

Techniques for the Evolution of Robust Pentose-fermenting Yeast for Bioconversion of Lignocellulose to Ethanol
14:53

Techniques for the Evolution of Robust Pentose-fermenting Yeast for Bioconversion of Lignocellulose to Ethanol

Published on: October 24, 2016

11.9K
Differential Imaging of Biological Structures with Doubly-resonant Coherent Anti-stokes Raman Scattering CARS
12:56

Differential Imaging of Biological Structures with Doubly-resonant Coherent Anti-stokes Raman Scattering CARS

Published on: October 17, 2010

14.1K

Related Experiment Videos

Last Updated: Feb 14, 2026

Establishing a Competing Risk Regression Nomogram Model for Survival Data
04:57

Establishing a Competing Risk Regression Nomogram Model for Survival Data

Published on: October 23, 2020

10.9K
Techniques for the Evolution of Robust Pentose-fermenting Yeast for Bioconversion of Lignocellulose to Ethanol
14:53

Techniques for the Evolution of Robust Pentose-fermenting Yeast for Bioconversion of Lignocellulose to Ethanol

Published on: October 24, 2016

11.9K
Differential Imaging of Biological Structures with Doubly-resonant Coherent Anti-stokes Raman Scattering CARS
12:56

Differential Imaging of Biological Structures with Doubly-resonant Coherent Anti-stokes Raman Scattering CARS

Published on: October 17, 2010

14.1K

Area of Science:

  • Statistics
  • Machine Learning
  • Data Science

Background:

  • Regularized regression is common for variable selection in linear models.
  • Existing methods often fail with outlier data points.
  • Robustness and efficiency are critical for reliable statistical modeling.

Purpose of the Study:

  • To develop a penalized regression procedure that is both robust to outliers and efficient.
  • To enable accurate variable selection and parameter estimation in the presence of erroneous data.
  • To satisfy oracle properties for enhanced statistical performance.

Main Methods:

  • A novel penalized procedure is proposed, incorporating adaptive weights.
  • Weights are applied to both the loss function and the penalty term.
  • Robustness is assessed using finite-sample breakdown points and influence functions.

Main Results:

  • The new method achieves maximum robustness and full efficiency.
  • It demonstrates sparse and robust solutions suitable for real-world data.
  • The proposed estimator attains the maximum breakdown point without efficiency loss under normal conditions.

Conclusions:

  • The developed penalized procedure offers a powerful tool for robust estimation and variable selection.
  • It effectively handles outliers while maintaining high statistical efficiency.
  • A computational algorithm is provided for practical application.