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

7.3K
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...
7.3K
Regression Analysis01:11

Regression Analysis

8.8K
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:
8.8K
Multiple Regression01:25

Multiple Regression

4.3K
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...
4.3K
Testing a Claim about Standard Deviation01:19

Testing a Claim about Standard Deviation

3.1K
A complete procedure to test a claim about population standard deviation or population variance is explained here.
The hypothesis testing for the claim of population standard deviation (or variance) requires the data and samples to be random and unbiased. The population distribution also must be normal. There is no specific requirement on the sample size as the estimation is based on the chi-square distribution.
As a first step, the hypothesis (null and alternative) concerning the claim about...
3.1K
Residuals and Least-Squares Property01:11

Residuals and Least-Squares Property

9.7K
The vertical distance between the actual value of y and the estimated value of y. In other words, it measures the vertical distance between the actual data point and the predicted point on the line
If the observed data point lies above the line, the residual is positive, and the line underestimates the actual data value for y. If the observed data point lies below the line, the residual is negative, and the line overestimates the actual data value for y.
The process of fitting the best-fit...
9.7K
Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

319
Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least...
319

You might also read

Related Articles

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

Sort by
Same author

Development and usability of a mobile ecological momentary assessment platform for dietary surveillance in the U.S.

The international journal of behavioral nutrition and physical activity·2026
Same author

Center and Geographic Variability in Acceptance of the First Donor Heart by Race.

Circulation. Heart failure·2026
Same author

Residential proximity to agricultural pesticide exposures during preconception and pregnancy and associations with Apgar scores in the Az-PEAR study (2006-2020).

Journal of exposure science & environmental epidemiology·2026
Same author

Contrast input and manual interventions significantly affect FreeSurfer morphometry and clinical correlations.

NeuroImage·2026
Same author

The influence of service dog partnerships on perceived and objective sleep quality for military veterans with PTSD.

Frontiers in sleep·2025
Same author

Development and Usability of a Mobile Ecological Momentary Assessment Platform for Dietary Surveillance in the U.S.

medRxiv : the preprint server for health sciences·2025
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
Same journal

Empirical likelihood inference for the area under the receiver operating characteristic (ROC) curve with verification biased data.

Statistical methods in medical research·2026
See all related articles

Related Experiment Video

Updated: Mar 19, 2026

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach
04:35

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach

Published on: July 3, 2020

3.8K

An approach for quantifying small effects in regression models.

Edward J Bedrick1, Lauren Hund2

  • 11 Department of Epidemiology and Biostatistics, Mel and Enid Zuckerman College of Public Health, University of Arizona, Tucson, AZ, USA.

Statistical Methods in Medical Research
|June 16, 2016
PubMed
Summary
This summary is machine-generated.

We introduce a new way to measure small effects in regression models by analyzing mean function variation, not just coefficients. This flexible approach is useful for detecting trends and comparing functions across groups.

Keywords:
Analysis of covarianceR-squaredinteractionnegligible effectstests for equivalence

More Related Videos

Probing the Limits of Egg Recognition Using Egg Rejection Experiments Along Phenotypic Gradients
07:34

Probing the Limits of Egg Recognition Using Egg Rejection Experiments Along Phenotypic Gradients

Published on: August 22, 2018

8.7K
Characterization of Complex Systems Using the Design of Experiments Approach: Transient Protein Expression in Tobacco as a Case Study
20:24

Characterization of Complex Systems Using the Design of Experiments Approach: Transient Protein Expression in Tobacco as a Case Study

Published on: January 31, 2014

17.2K

Related Experiment Videos

Last Updated: Mar 19, 2026

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach
04:35

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach

Published on: July 3, 2020

3.8K
Probing the Limits of Egg Recognition Using Egg Rejection Experiments Along Phenotypic Gradients
07:34

Probing the Limits of Egg Recognition Using Egg Rejection Experiments Along Phenotypic Gradients

Published on: August 22, 2018

8.7K
Characterization of Complex Systems Using the Design of Experiments Approach: Transient Protein Expression in Tobacco as a Case Study
20:24

Characterization of Complex Systems Using the Design of Experiments Approach: Transient Protein Expression in Tobacco as a Case Study

Published on: January 31, 2014

17.2K

Area of Science:

  • Statistics
  • Econometrics
  • Biostatistics

Background:

  • Quantifying small effects in regression models is crucial for accurate data interpretation.
  • Existing methods often focus on regression coefficients, potentially missing subtle variations.
  • Diverse scientific fields require robust methods for detecting subtle trends and group differences.

Purpose of the Study:

  • To present a novel approach for quantifying small effects in regression models.
  • To offer an alternative method focusing on variation in the mean function.
  • To demonstrate the applicability of the method in various statistical contexts.

Main Methods:

  • Developed a novel statistical approach based on analyzing variation in the mean function.
  • Proposed straightforward Bayesian methods for statistical inference.
  • Applied the method to diverse settings including trend testing and group comparisons.

Main Results:

  • The proposed method effectively quantifies small effects by examining mean function variation.
  • Bayesian inference provides a robust framework for assessing these effects.
  • Illustrative examples demonstrate the method's utility in practical scenarios.

Conclusions:

  • The novel approach offers a valuable tool for quantifying small effects in regression analysis.
  • Focusing on mean function variation provides a complementary perspective to coefficient-based methods.
  • The Bayesian framework ensures reliable inference for diverse applications.