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

Nonlinear Pharmacokinetics: Causes of Nonlinearity01:22

Nonlinear Pharmacokinetics: Causes of Nonlinearity

744
Nonlinearity in drug pharmacokinetics is caused by various factors influencing how a drug is absorbed, distributed, metabolized, and excreted. Understanding these nonlinear processes is crucial for predicting drug behavior in the body and optimizing drug dosing regimens.
Nonlinear drug absorption can occur when the process is rate-limited by solubility, carrier-mediated transport systems, or saturation of the presystemic gut wall or hepatic metabolism. For instance, high doses of riboflavin...
744
Parameters Affecting Nonlinear Elimination: Zero-Order Input, First-Order Absorption and Two-Compartment Model01:13

Parameters Affecting Nonlinear Elimination: Zero-Order Input, First-Order Absorption and Two-Compartment Model

322
Drugs administered through various routes can lead to nonlinear elimination, resulting in complex pharmacokinetic behaviors crucial to understanding efficacious drug dosing.
When a drug is administered through a constant intravenous infusion and eliminated via nonlinear pharmacokinetics, it follows zero-order input. For example, oral drugs undergo first-order absorption upon administration and are eliminated through nonlinear pharmacokinetics.
In the case of subcutaneously administered drugs,...
322
Application of Nonlinear Inequalities01:29

Application of Nonlinear Inequalities

266
A nonlinear inequality describes a comparison involving an expression that curves or behaves more complexly than a straight line. These inequalities often appear in forms that include squares, products, or variables in the denominator.To solve such an inequality, one starts by rewriting it so that zero appears on one side. For example, the inequality:  can be factored as: This form makes it easier to identify the values that cause the expression to equal zero. In this case, the...
266
Introduction to Nonlinear Inequalities01:25

Introduction to Nonlinear Inequalities

234
Linear and nonlinear inequalities are fundamental for analyzing variable relationships and identifying ranges satisfying specific conditions. A linear inequality involves variables raised only to the first power, resulting in a straight-line graph. This line partitions the coordinate plane into two distinct regions: one that satisfies the inequality and one that does not. Each region represents a set of solutions where the linear relationship holds true under the specified constraint.Nonlinear...
234
Extraction: Partition and Distribution Coefficients01:14

Extraction: Partition and Distribution Coefficients

4.9K
The distribution law or Nernst's distribution law is the law that governs the distribution of a solute between two immiscible solvents. This law, also known as the partition law, states that if a solute is added to the mixture of two immiscible solvents at a constant temperature, the solute is distributed between the two solvents in such a way that the ratio of solute concentrations in the solvents remains constant at equilibrium.
For extracting a solute from an aqueous phase into an...
4.9K
Nonlinear Pharmacokinetics: Overview01:19

Nonlinear Pharmacokinetics: Overview

1.1K
Nonlinear or dose-dependent pharmacokinetics is a phenomenon that occurs when the pharmacokinetic parameters of certain drugs deviate from linear pharmacokinetics at higher doses. These drugs do not follow the expected first-order kinetics, where the rate of drug elimination is directly proportional to the drug concentration. Instead, they exhibit a nonlinear relationship, which can be attributed to several factors.
Nonlinearity can arise due to the saturation of plasma protein-binding or...
1.1K

You might also read

Related Articles

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

Sort by
Same author

Balancing burden and resolution: Effects of EMA survey schedule on compliance and study evaluation in suicide-focused research.

Journal of psychiatric research·2026
Same author

Surfacing Suicidal Risk Through Simulated Social Interaction: Per-Person Language Model Agents as Communicative Stress Tests.

medRxiv : the preprint server for health sciences·2026
Same author

The dynamic relationship between alcohol and suicidal ideation: Between-person associations and overnight inertia.

Journal of affective disorders·2026
Same author

Influences of adverse childhood experiences and weekly pregnancy stress on postpartum mental health symptoms: a machine learning examination.

Archives of women's mental health·2026
Same author

Blending substantive and methodological expertise into statistical models: Longitudinal model development.

The British journal of mathematical and statistical psychology·2026
Same author

Predicting Momentary Suicidal Ideation From Smartphone Screenshots Using Vision-Language Models: Prospective Machine Learning Study.

JMIR mental health·2026

Related Experiment Video

Updated: Feb 11, 2026

Herbs-Partitioned Moxibustion on the Navel in a Rat Model of Primary Dysmenorrhea with Cold Coagulation and Blood Stasis
05:36

Herbs-Partitioned Moxibustion on the Navel in a Rat Model of Primary Dysmenorrhea with Cold Coagulation and Blood Stasis

Published on: October 4, 2024

1.2K

Recursive Partitioning with Nonlinear Models of Change.

Gabriela Stegmann1, Ross Jacobucci2, Sarfaraz Serang3

  • 1a Department of Psychology , Arizona State University , Tempe , Arizona , USA.

Multivariate Behavioral Research
|April 24, 2018
PubMed
Summary

This study introduces nonlinear longitudinal recursive partitioning (nLRP) for analyzing nonlinear longitudinal trajectories. The method uses decision trees and mixed-effects models to predict differences in developmental patterns.

Keywords:
Longitudinal recursive partitioningdecision treesgrowthcurve modellongitudinal datanonlinear mixed-effects models

More Related Videos

Determination of Plasma Membrane Partitioning for Peripherally-associated Proteins
11:11

Determination of Plasma Membrane Partitioning for Peripherally-associated Proteins

Published on: June 15, 2018

8.8K
Measurement of Scattering Nonlinearities from a Single Plasmonic Nanoparticle
15:06

Measurement of Scattering Nonlinearities from a Single Plasmonic Nanoparticle

Published on: January 3, 2016

13.4K

Related Experiment Videos

Last Updated: Feb 11, 2026

Herbs-Partitioned Moxibustion on the Navel in a Rat Model of Primary Dysmenorrhea with Cold Coagulation and Blood Stasis
05:36

Herbs-Partitioned Moxibustion on the Navel in a Rat Model of Primary Dysmenorrhea with Cold Coagulation and Blood Stasis

Published on: October 4, 2024

1.2K
Determination of Plasma Membrane Partitioning for Peripherally-associated Proteins
11:11

Determination of Plasma Membrane Partitioning for Peripherally-associated Proteins

Published on: June 15, 2018

8.8K
Measurement of Scattering Nonlinearities from a Single Plasmonic Nanoparticle
15:06

Measurement of Scattering Nonlinearities from a Single Plasmonic Nanoparticle

Published on: January 3, 2016

13.4K

Area of Science:

  • Statistics
  • Biostatistics
  • Developmental Science

Background:

  • Longitudinal data analysis is crucial for understanding developmental changes.
  • Existing methods may not fully capture complex nonlinear trajectories.
  • Recursive partitioning offers a way to identify subgroups within longitudinal data.

Purpose of the Study:

  • To introduce nonlinear longitudinal recursive partitioning (nLRP) for analyzing nonlinear longitudinal trajectories.
  • To present the R package longRpart2 for implementing the nLRP method.
  • To extend existing longitudinal recursive partitioning methods to accommodate nonlinear mixed-effects models.

Main Methods:

  • Nonlinear longitudinal recursive partitioning (nLRP) using decision trees.
  • Estimation of user-specified linear or nonlinear mixed-effects models at each node.
  • Application of the longRpart2 R package for data analysis.

Main Results:

  • The nLRP method effectively identifies distinct nonlinear longitudinal trajectories.
  • The longRpart2 package provides a practical tool for implementing nLRP.
  • Empirical data from the Early Childhood Longitudinal Study-Kindergarten Cohort illustrates the method's utility.

Conclusions:

  • nLRP is a valuable extension for analyzing complex nonlinear longitudinal data.
  • The method allows for the prediction of differences in trajectories based on individual-level covariates.
  • This approach enhances the understanding of developmental patterns in cohort studies.