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

Mechanistic Models: Compartment Models in Individual and Population Analysis

Mechanistic Models: Compartment Models in Individual and Population Analysis

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 squares (OLS)...

Naturalistic Observations

Naturalistic Observations

If you want to understand how behavior occurs, one of the best ways to gain information is to simply observe the behavior in its natural context. However, people might change their behavior in unexpected ways if they know they are being observed. How do researchers obtain accurate information when people tend to hide their natural behavior? As an example, imagine that your professor asks everyone in your class to raise their hand if they always wash their hands after using the restroom. Chances...

Multicompartment Models: Overview

Multicompartment Models: Overview

Multicompartment models are mathematical constructs that depict how drugs are distributed and eliminated within the body. They segment the body into several compartments, symbolizing various physiological or anatomical areas connected through drug transfer processes such as absorption, metabolism, distribution, and elimination.
These models offer a more comprehensive representation of drug behavior in the body than one-compartment models. They accommodate the complexity of drug distribution,...

State Space Representation

State Space Representation

The frequency-domain technique, commonly used in analyzing and designing feedback control systems, is effective for linear, time-invariant systems. However, it falls short when dealing with nonlinear, time-varying, and multiple-input multiple-output systems. The time-domain or state-space approach addresses these limitations by utilizing state variables to construct simultaneous, first-order differential equations, known as state equations, for an nth-order system.
Consider an RLC circuit, a...

Observational Studies

Observational Studies

Observational studies are a type of analytical study where researchers observe events without any interventions. In other words, the researcher does not influence the response variable or the experiment's outcome.
There are three types of observational studies – Prospective, retrospective, and cross-sectional.
Prospective Study
Prospective studies, also known as longitudinal or cohort studies, are carried out by collecting future data from groups sharing similar characteristics. One example of...

Assumptions of Survival Analysis

Assumptions of Survival Analysis

Survival models analyze the time until one or more events occur, such as death in biological organisms or failure in mechanical systems. These models are widely used across fields like medicine, biology, engineering, and public health to study time-to-event phenomena. To ensure accurate results, survival analysis relies on key assumptions and careful study design.

You might also read

Related Articles

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

Sort by

Same author

Cerebrovascular Events in Systemic Lupus Erythematosus: Results From an International Inception Cohort Study.

Arthritis care & research·2018

Same author

Triboelectrification-Induced Self-Assembly of Macro-Sized Polymer Beads on a Nanostructured Surface for Self-Powered Patterning.

ACS nano·2018

Same author

Accommodating informative dropout and death: a joint modelling approach for longitudinal and semi-competing risks data.

Journal of the Royal Statistical Society. Series C, Applied statistics·2017

Same author

Ultraviolet-Ray-Induced Sea Cucumber (Stichopus japonicus) Melting Is Mediated by the Caspase-Dependent Mitochondrial Apoptotic Pathway.

Journal of agricultural and food chemistry·2017

Same author

Hydrogen Treatment Protects Mice Against Chronic Pancreatitis by Restoring Regulatory T Cells Loss.

Cellular physiology and biochemistry : international journal of experimental cellular physiology, biochemistry, and pharmacology·2017

Same author

Optimized ROI size on ADC measurements of normal pancreas, pancreatic cancer and mass-forming chronic pancreatitis.

Oncotarget·2017

Search research articles

Related Experiment Video

Updated: Jun 11, 2026

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

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

Published on: December 9, 2015

A multistate model for events defined by prolonged observation.

Vernon T Farewell¹, Li Su

¹MRC Biostatistics Unit, Institute of Public Health, University Forvie Site, Robinson Way, Cambridge CB2 0SR, UK. vern.farewell@mrc-bsu.cam.ac.uk

Biostatistics (Oxford, England)

|June 29, 2010

Summary

This summary is machine-generated.

This study introduces a 3-state model to accurately analyze time-to-event data when events require a prolonged condition, like psoriatic arthritis remission. This approach improves upon existing 2-state models for clinical meaningfulness.

Related Experiment Videos

Last Updated: Jun 11, 2026

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

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

Published on: December 9, 2015

Area of Science:

Biostatistics
Clinical Epidemiology
Rheumatology

Background:

Time-to-event analyses face challenges when events are defined by prolonged states.
Psoriatic arthritis remission is a key example requiring duration considerations.

Purpose of the Study:

To propose and evaluate a 3-state model for time-to-event analyses of prolonged conditions.
To improve the clinical meaningfulness of remission duration in psoriatic arthritis studies.

Main Methods:

Development of a 3-state model to capture transitions into and out of remission.
Linking remission states to initial and subsequent states to incorporate duration.
Comparison with existing 2-state models using different entry time definitions.

Main Results:

The proposed 3-state model offers a more nuanced characterization of remission duration.
Alternative 2-state models may oversimplify or misrepresent the duration of remission.
The model accounts for the clinical requirement of sustained remission.

Conclusions:

A 3-state model is superior for analyzing time-to-event data with prolonged event definitions.
This methodology enhances the accuracy and clinical relevance of analyses, particularly for psoriatic arthritis remission.
The proposed model provides a robust framework for future research in similar conditions.