Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Application of Nonlinear Inequalities

Application of Nonlinear Inequalities

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 key values are 3...

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...

Linear Approximation in Time Domain

Linear Approximation in Time Domain

Nonlinear systems often require sophisticated approaches for accurate modeling and analysis, with state-space representation being particularly effective. This method is especially useful for systems where variables and parameters vary with time or operating conditions, such as in a simple pendulum or a translational mechanical system with nonlinear springs.
For a simple pendulum with a mass evenly distributed along its length and the center of mass located at half the pendulum's length, the...

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

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

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,...

Classification of Systems-I

Classification of Systems-I

Linearity is a system property characterized by a direct input-output relationship, combining homogeneity and additivity.
Homogeneity dictates that if an input x(t) is multiplied by a constant c, the output y(t) is multiplied by the same constant. Mathematically, this is expressed as:

Linear time-invariant Systems

Linear time-invariant Systems

A system is linear if it displays the characteristics of homogeneity and additivity, together termed the superposition property. This principle is fundamental in all linear systems. Linear time-invariant (LTI) systems include systems with linear elements and constant parameters.
The input-output behavior of an LTI system can be fully defined by its response to an impulsive excitation at its input. Once this impulse response is known, the system's reaction to any other input can be calculated...

You might also read

Related Articles

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

Sort by

Same author

Microfluidization-Driven Structural Reorganization and Functional Improvements of Whole Chickpea Flour.

Foods (Basel, Switzerland)·2026

Same author

CIT-Lasso: a scalable approach beyond guilty by association for identifying causal variants from genome-wide summary statistics.

Genome biology·2026

Same author

Early Mucosal Type II Interferon Limits SARS-CoV-2 Replication in Humans.

medRxiv : the preprint server for health sciences·2026

Same author

Evaluation of Large Language Models for Structured Data Extraction From Interstitial Lung Disease Clinical Notes: Comparative Study.

Journal of medical Internet research·2026

Same author

Design of an artificial intelligence model to screen spontaneous speech to detect Alzheimer's Disease.

PLOS digital health·2026

Same author

A proteogenomic RNA processing mechanism drives sex differences in meningioma.

Research square·2026

Search research articles

Related Experiment Video

Updated: May 12, 2026

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

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

Published on: January 31, 2014

Constrained Design of a Binary Instrument in a Partially Linear Model.

Tim Morrison¹, Minh Nguyen², Jonathan Chen²

¹Statistics Stanford University.

Observational Studies

|May 11, 2026

Summary

This study introduces a two-stage method for optimal assignment of nudges in randomized encouragement designs to improve local average treatment effect (LATE) estimation. The approach offers a convex design criterion for efficient and constrained LATE estimation.

Keywords:

Design of experiments Instrumental variables Partially linear models Randomized controlled trials Regression discontinuity

More Related Videos

Efficient Sampling of Genetically Encoded Biosensor Design Space Enabled with a Design of Experiments and Automation Workflow

Efficient Sampling of Genetically Encoded Biosensor Design Space Enabled with a Design of Experiments and Automation Workflow

Published on: October 17, 2025

Related Experiment Videos

Last Updated: May 12, 2026

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

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

Published on: January 31, 2014

Efficient Sampling of Genetically Encoded Biosensor Design Space Enabled with a Design of Experiments and Automation Workflow

Efficient Sampling of Genetically Encoded Biosensor Design Space Enabled with a Design of Experiments and Automation Workflow

Published on: October 17, 2025

Area of Science:

Econometrics
Causal Inference
Experimental Design

Background:

Randomized encouragement designs are used to estimate treatment effects when compliance is imperfect.
Assigning nudges effectively is crucial for accurate estimation of the local average treatment effect (LATE).
Existing methods may not be optimal for covariate-dependent nudge assignment.

Purpose of the Study:

To develop an optimal strategy for assigning nudges based on covariates in randomized encouragement studies.
To improve the estimation of the local average treatment effect (LATE) under a partially linear model.
To provide a flexible design criterion that accommodates practical constraints.

Main Methods:

A two-stage procedure is proposed for consistent and optimal LATE estimation.
A partially linear model is assumed, with a non-parametric baseline and linear treatment effect.
A finite sample approximation of the LATE variance is derived to create a convex design criterion for minimization.

Main Results:

The proposed two-stage method consistently and optimally estimates the LATE.
The derived design criterion is convex, allowing for incorporation of budgetary or ethical constraints.
The method demonstrated significant gains compared to a regression discontinuity design in a semi-synthetic emergency department triage example.

Conclusions:

The developed two-stage procedure offers an optimal approach for nudge assignment in randomized encouragement studies.
The method provides a practical and efficient way to estimate LATE, even with constraints.
This approach shows promise for improving causal inference in observational and experimental settings.