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

Residuals and Least-Squares Property01:11

Residuals and Least-Squares Property

8.3K
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...
8.3K
Multiple Regression01:25

Multiple Regression

3.4K
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...
3.4K
Calibration Curves: Linear Least Squares01:20

Calibration Curves: Linear Least Squares

3.5K
A calibration curve is a plot of the instrument's response against a series of known concentrations of a substance. This curve is used to set the instrument response levels, using the substance and its concentrations as standards. Alternatively, or additionally, an equation is fitted to the calibration curve plot and subsequently used to calculate the unknown concentrations of other samples reliably.
For data that follow a straight line, the standard method for fitting is the linear...
3.5K
Response Surface Methodology01:16

Response Surface Methodology

379
Response Surface Methodology (RSM) is a collection of statistical and mathematical techniques used to develop, improve, and optimize processes. It is particularly valuable when many input variables or factors potentially influence a response variable.
The process of RSM involves several key steps:
379
Analysis of Population Pharmacokinetic Data01:12

Analysis of Population Pharmacokinetic Data

531
Analysis of population pharmacokinetic data involves studying the behavior of drugs within diverse populations to understand their pharmacokinetic parameters. Traditional pharmacokinetic methods typically involve collecting samples from a few individuals and estimating these parameters. While these methods are commonly used, they have limitations in capturing the variability in drug response among individuals or heterogeneous populations. Population pharmacokinetics is employed to address these...
531
Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

140
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...
140

You might also read

Related Articles

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

Sort by
Same author

Oxymatrine alleviates cerebral ischemia-reperfusion injury by inhibiting microglia ferroptosis via NRF2 pathway activation.

Phytomedicine : international journal of phytotherapy and phytopharmacology·2026
Same author

4d orbital ruthenium doping enables high-capacity and stable α-MnO<sub>2</sub> cathodes for aqueous zinc-ion batteries.

Dalton transactions (Cambridge, England : 2003)·2026
Same author

Activation of mitophagy via miR-223/NLRP3 axis ameliorates dopaminergic neuronal damage in parkinson's disease.

Metabolic brain disease·2026
Same author

Long-term Retrospective Study on Survival and Cardiac Function Improvement in Heart Failure Patients with Atrial Fibrillation Treated With Radiofrequency Ablation.

Kardiologiia·2026
Same author

Corrigendum to "Carnosine protects against cerebral ischemia/reperfusion injury through promoting microglial M2 polarization via SIRT1/NF-κB signaling pathway" [Europ. J. Pharmacol. 1007 (2025) 178191].

European journal of pharmacology·2025
Same author

Carnosine protects against cerebral ischemia/reperfusion injury through promoting microglial M2 polarization via SIRT1/NF-κB signaling pathway.

European journal of pharmacology·2025
Same journal

A KL-divergence-based test for elliptical distribution.

Journal of nonparametric statistics·2026
Same journal

Soft Bayesian Additive Regression Trees (SBART) for correlated survey response with non-Gaussian error.

Journal of nonparametric statistics·2026
Same journal

A comparison of causal inference methods for evaluating multiple treatment groups.

Journal of nonparametric statistics·2025
Same journal

Regression analysis of multiplicative hazards model with time-dependent coefficient for sparse longitudinal covariates.

Journal of nonparametric statistics·2025
Same journal

TSSS: A Novel Triangulated Spherical Spline Smoothing for Surface-Based Data.

Journal of nonparametric statistics·2025
Same journal

Nonparametric Density Estimation for Data Scattered on Irregular Spatial Domains: A Likelihood-Based Approach Using Bivariate Penalized Spline Smoothing.

Journal of nonparametric statistics·2025
See all related articles

Related Experiment Video

Updated: Nov 11, 2025

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
10:46

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data

Published on: December 9, 2015

10.8K

Local polynomial regression for pooled response data.

Dewei Wang1, Xichen Mou2, Xiang Li3

  • 1Department of Statistics, University of South Carolina, Columbia, South Carolina, U.S.A.

Journal of Nonparametric Statistics
|March 25, 2021
PubMed
Summary
This summary is machine-generated.

We developed new statistical methods for analyzing pooled data to estimate conditional means. These local polynomial estimators improve accuracy when working with grouped responses in various settings.

Keywords:
62G0862G20cross validationhomogeneous poolingrandom pooling

More Related Videos

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

3.5K
Systems Analysis of the Neuroinflammatory and Hemodynamic Response to Traumatic Brain Injury
07:21

Systems Analysis of the Neuroinflammatory and Hemodynamic Response to Traumatic Brain Injury

Published on: May 27, 2022

3.4K

Related Experiment Videos

Last Updated: Nov 11, 2025

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
10:46

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data

Published on: December 9, 2015

10.8K
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

3.5K
Systems Analysis of the Neuroinflammatory and Hemodynamic Response to Traumatic Brain Injury
07:21

Systems Analysis of the Neuroinflammatory and Hemodynamic Response to Traumatic Brain Injury

Published on: May 27, 2022

3.4K

Area of Science:

  • Statistics
  • Econometrics
  • Biostatistics

Background:

  • Analyzing continuous response data often involves challenges with pooled samples.
  • Existing methods may not fully address the complexities introduced by different pooling designs.

Purpose of the Study:

  • To introduce novel local polynomial estimators for conditional mean estimation using pooled response data.
  • To investigate the asymptotic properties and compare the performance of these new estimators.

Main Methods:

  • Development of local polynomial estimators tailored for pooled data.
  • Theoretical analysis of asymptotic properties.
  • Extensive simulation studies across diverse model settings and pooling strategies.

Main Results:

  • The proposed estimators demonstrate robust finite sample performance.
  • Comparisons reveal advantages under various pooling designs and model complexities.
  • Successful application to two real-life datasets validated practical utility.

Conclusions:

  • Local polynomial estimation provides an effective approach for conditional mean analysis with pooled data.
  • The developed methods offer improved accuracy and practical applicability in statistical modeling.
  • These estimators are valuable tools for researchers dealing with grouped response variables.