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

Prediction Intervals01:03

Prediction Intervals

3.5K
The interval estimate of any variable is known as the prediction interval. It helps decide if a point estimate is dependable.
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y. 
3.5K
Clearance Models: Noncompartmental Models01:17

Clearance Models: Noncompartmental Models

331
Clearance is a pharmacokinetic parameter traditionally defined by compartment models, signifying the rate at which a drug is expelled from the body. However, a noncompartmental model offers an alternative method for assessing clearance, primarily employing empirical data obtained after administering a single drug dose.
The noncompartmental approach capitalizes on extensive sampling data, correlating the volume of distribution to systemic exposure and the administered dosage. This method enables...
331
One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation01:24

One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation

1.3K
This lesson introduces two critical methods in pharmacokinetics, the Wagner-Nelson and Loo-Riegelman methods, used for estimating the absorption rate constant (ka) for drugs administered via non-intravenous routes. The Wagner-Nelson method relates ka to the plasma concentration derived from the slope of a semilog percent unabsorbed time plot. However, it is limited to drugs with one-compartment kinetics and can be impacted by factors like gastrointestinal motility or enzymatic degradation.
On...
1.3K
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
Statistical Inference Techniques in Hypothesis Testing: Parametric Versus Nonparametric Data01:16

Statistical Inference Techniques in Hypothesis Testing: Parametric Versus Nonparametric Data

564
Statistical inference techniques, paramount in hypothesis testing, differentiate into two broad categories: parametric and nonparametric statistics.
Parametric statistics, as the name suggests, assumes that data follow a specific distribution, often a normal distribution. This assumption enables robust hypothesis testing and estimation. Parametric methods, like the Student's t-test or Goodness-of-fit test, are frequently employed in biostatistics due to their robustness. For instance,...
564
Parametric Survival Analysis: Weibull and Exponential Methods01:14

Parametric Survival Analysis: Weibull and Exponential Methods

1.2K
Parametric survival analysis models survival data by assuming a specific probability distribution for the time until an event occurs. The Weibull and exponential distributions are two of the most commonly used methods in this context, due to their versatility and relatively straightforward application.
Weibull Distribution
The Weibull distribution is a flexible model used in parametric survival analysis. It can handle both increasing and decreasing hazard rates, depending on its shape parameter...
1.2K

You might also read

Related Articles

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

Sort by
Same author

Long-read deep sequencing reveals high rates of multilineage transmission and rapid viral population changes in acute HIV infection.

Nature communications·2026
Same author

Searching for immune correlates in Lassa vaccine development - workshop report.

NPJ vaccines·2026
Same author

Correlates of severe and delta COVID-19 in a phase 3 trial of the AZD1222 vaccine.

NPJ vaccines·2026
Same author

Influence of the broadly neutralizing antibody VRC01 on HIV breakthrough virus populations in antibody-mediated prevention trials.

Nature communications·2026
Same author

Impact of prior SARS-CoV-2 acquisition on binding and neutralizing antibody responses following COVID-19 vaccination: A cross-protocol analysis of individual-level data from six phase 3 clinical trials.

Vaccine·2026
Same author

The neutralizing antibody titer correlate of COVID-19 risk in the COVID-19 variant immunologic landscape (COVAIL) trial was not modified by SARS-CoV-2 amino acid sequence distances.

Vaccine·2026
Same journal

Fast penalized generalized estimating equations for large longitudinal functional datasets.

Biometrics·2026
Same journal

Causally-interpretable random-effects meta-analysis.

Biometrics·2026
Same journal

Statistical inference for mean function of partially observed functional time series.

Biometrics·2026
Same journal

Subgroup identification via Interaction Tree and Mixed Model for Repeated Measures with application to Alzheimer's disease.

Biometrics·2026
Same journal

Finite mixtures of linear quantile regressions with concomitant variables: a solution to endogeneity in longitudinal data modeling.

Biometrics·2026
Same journal

Discussion on "INTACT: a method for integration of longitudinal physical activity data from multiple sources" by Jingru Zhang, Erjia Cui, Hongzhe Li, and Haochang Shou.

Biometrics·2026
See all related articles

Related Experiment Video

Updated: Mar 11, 2026

Psychophysically-anchored, Robust Thresholding in Studying Pain-related Lateralization of Oscillatory Prestimulus Activity
07:28

Psychophysically-anchored, Robust Thresholding in Studying Pain-related Lateralization of Oscillatory Prestimulus Activity

Published on: January 21, 2017

7.4K

Model-robust inference for continuous threshold regression models.

Youyi Fong1, Chongzhi Di1, Ying Huang1

  • 1Fred Hutchinson Cancer Research Center, Seattle Washington 98109, U.S.A.

Biometrics
|November 19, 2016
PubMed
Summary
This summary is machine-generated.

This study introduces continuous threshold regression models for analyzing infectious disease transmission data. The methods provide reliable statistical inference for immune response biomarkers, balancing flexibility and simplicity.

Keywords:
Mother-to-child transmission of HIV-1Profile likelihood ratio under model misspecificationRV144 immune correlates studiesRegression kink

More Related Videos

A Tactile Automated Passive-Finger Stimulator TAPS
19:44

A Tactile Automated Passive-Finger Stimulator TAPS

Published on: June 3, 2009

14.2K
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

Related Experiment Videos

Last Updated: Mar 11, 2026

Psychophysically-anchored, Robust Thresholding in Studying Pain-related Lateralization of Oscillatory Prestimulus Activity
07:28

Psychophysically-anchored, Robust Thresholding in Studying Pain-related Lateralization of Oscillatory Prestimulus Activity

Published on: January 21, 2017

7.4K
A Tactile Automated Passive-Finger Stimulator TAPS
19:44

A Tactile Automated Passive-Finger Stimulator TAPS

Published on: June 3, 2009

14.2K
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

Area of Science:

  • Statistics
  • Biostatistics
  • Epidemiology

Background:

  • Threshold regression models analyze outcome-covariate relationships that change at a specific covariate value.
  • Continuous threshold models offer a flexible yet simple approach, avoiding abrupt changes at the threshold.
  • Applications include analyzing immune response biomarkers in infectious disease transmission studies.

Purpose of the Study:

  • To develop and evaluate methods for estimating and performing inference on continuous threshold regression models.
  • To address challenges in statistical inference, particularly under model misspecification.
  • To provide practical guidelines for applying these models in real-world data analysis, such as HIV-1 immune correlates studies.

Main Methods:

  • Derivation of the limiting distribution for the maximum likelihood estimator.
  • Development of Wald and test-inversion confidence intervals for robust inference.
  • Evaluation of finite sample performance and comparison with bootstrap confidence intervals.

Main Results:

  • The proposed methods for estimating continuous threshold models are statistically sound.
  • Wald and test-inversion confidence intervals demonstrate reliable performance in finite samples.
  • Guidelines are provided to aid practitioners in selecting appropriate methods for data analysis.

Conclusions:

  • Continuous threshold regression models offer a valuable tool for understanding complex biological associations.
  • The developed inferential methods provide robust statistical support for biomarker analysis in infectious diseases.
  • The study enhances the application of statistical modeling in public health research, particularly for HIV-1 studies.