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

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

498
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...
498
Survival Tree01:19

Survival Tree

85
Survival trees are a non-parametric method used in survival analysis to model the relationship between a set of covariates and the time until an event of interest occurs, often referred to as the "time-to-event" or "survival time." This method is particularly useful when dealing with censored data, where the event has not occurred for some individuals by the end of the study period, or when the exact time of the event is unknown.
 Building a Survival Tree
Constructing a...
85
Residuals and Least-Squares Property01:11

Residuals and Least-Squares Property

7.4K
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...
7.4K
Calibration Curves: Linear Least Squares01:20

Calibration Curves: Linear Least Squares

1.3K
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...
1.3K
Quantifying and Rejecting Outliers: The Grubbs Test01:02

Quantifying and Rejecting Outliers: The Grubbs Test

1.6K
Sometimes, a data set can have a recorded numerical observation that greatly  deviates from the rest of the data. Assuming that the data is normally distributed, a statistical method called the Grubbs test can be used to determine whether the observation is truly an outlier.  To perform a two-tailed Grubbs test, first, calculate the absolute difference between the outlier and the mean. Then, calculate the ratio between this difference and the standard deviation of the sample. This...
1.6K
Routh-Hurwitz Criterion II01:19

Routh-Hurwitz Criterion II

246
In the application of the Routh-Hurwitz criterion, two specific scenarios can arise that complicate stability analysis.
The first scenario occurs when a singular zero appears in the first column of the Routh table. This situation creates a division by zero issues. To resolve this, a small positive or negative number, denoted as epsilon (∈), is substituted for the zero. The stability analysis proceeds by assuming a sign for ∈. If ∈ is positive, any sign change in the first...
246

You might also read

Related Articles

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

Sort by
Same author

Comparison of Different Methods for the Meta-Analysis of Diagnostic Test Accuracy Studies-A Simulation Study.

Biometrical journal. Biometrische Zeitschrift·2026
Same author

When to Adjust for Multiple Testing: A Unifying Guiding Principle.

Biometrical journal. Biometrische Zeitschrift·2026
Same author

Burnout and Work-Life Balance: A Longitudinal Study Into the Transition From Medical School to Postgraduate Training.

Deutsches Arzteblatt international·2026
Same author

Associations of perceived family economy, registry-based parental education and income with adolescent psychological distress: the Young-HUNT cross-sectional studies 2006-2008 and 2017-2019.

BMJ open·2026
Same author

Agreement of minimally invasive pulse wave analysis with pulmonary artery and transpulmonary thermodilution cardiac output measurements in perioperative and intensive care medicine: a systematic review and meta-analysis.

British journal of anaesthesia·2026
Same author

[Training conditions in postgraduate family medicine training in Bavaria and the role of the Competence Center: A comparative cross-sectional study].

Zeitschrift fur Evidenz, Fortbildung und Qualitat im Gesundheitswesen·2026
Same journal

Editorial: The MASLD spectrum: an emerging epidemic of cardiometabolic and extra-hepatic dimensions.

Frontiers in epidemiology·2026
Same journal

The persistence and mortality of Lassa fever in Nigeria reflect systemic clinical and diagnostic challenges rather than viral reemergence alone.

Frontiers in epidemiology·2026
Same journal

Incidence, prevalence, and prognostic impact of sarcopenia on hepatic and cardiovascular outcomes in non-cirrhotic metabolic dysfunction-associated steatotic liver disease.

Frontiers in epidemiology·2026
Same journal

Modeling the disruptive impact of the COVID-19 pandemic on nurses' supply and wages.

Frontiers in epidemiology·2026
Same journal

HIV-1 late diagnosis in Cabo Verde: associated factors and implications for preventive strategies.

Frontiers in epidemiology·2026
Same journal

Ventilator-associated pneumonia among intensive care nurses: a multicenter cross-sectional study on knowledge and preventive measures in intensive care units of Mogadishu, Somalia.

Frontiers in epidemiology·2026
See all related articles

Related Experiment Video

Updated: Jul 1, 2025

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
07:35

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

7.5K

Greedy knot selection algorithm for restricted cubic spline regression.

Jo Inge Arnes1, Alexander Hapfelmeier2, Alexander Horsch1

  • 1Department of Computer Science, Faculty of Science and Technology, UiT The Arctic University of Norway, Tromsø, Norway.

Frontiers in Epidemiology
|March 8, 2024
PubMed
Summary
This summary is machine-generated.

Restricted cubic spline (RCS) regression knot selection can cause overfitting or underperformance. A new backward greedy search algorithm improves prediction error and model fit, offering a better approach for epidemiological modeling.

Keywords:
algorithmmodel selectionnon-linear regressionpredictionrestricted cubic splines

More Related Videos

Quantification of Strain in a Porcine Model of Skin Expansion Using Multi-View Stereo and Isogeometric Kinematics
14:14

Quantification of Strain in a Porcine Model of Skin Expansion Using Multi-View Stereo and Isogeometric Kinematics

Published on: April 16, 2017

11.6K
Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
11:53

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm

Published on: December 9, 2012

13.0K

Related Experiment Videos

Last Updated: Jul 1, 2025

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
07:35

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

7.5K
Quantification of Strain in a Porcine Model of Skin Expansion Using Multi-View Stereo and Isogeometric Kinematics
14:14

Quantification of Strain in a Porcine Model of Skin Expansion Using Multi-View Stereo and Isogeometric Kinematics

Published on: April 16, 2017

11.6K
Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
11:53

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm

Published on: December 9, 2012

13.0K

Area of Science:

  • Epidemiology
  • Statistical modeling

Background:

  • Non-linear regression, including restricted cubic spline (RCS) regression, is crucial in epidemiology for prediction and estimating variable relationships.
  • Standard RCS knot placement using quantiles can lead to overfitting in dense data regions or underperformance in sparse regions.

Purpose of the Study:

  • To develop and evaluate a novel knot selection method for restricted cubic spline regression.
  • To address the limitations of standard quantile-based knot placement in epidemiological models.

Main Methods:

  • A greedy search algorithm utilizing a backward selection approach for knot placement in RCS regression.
  • Implementation of the algorithm within an open-source R-package named 'knutar'.
  • Comparison of the proposed method against the standard knot selection process via simulation experiments.

Main Results:

  • The proposed backward greedy search algorithm demonstrated reduced prediction error compared to the standard method.
  • The algorithm also yielded improved Bayesian information criterion scores, indicating better model fit.
  • Simulation experiments confirmed the effectiveness of the new knot selection strategy.

Conclusions:

  • The developed greedy backward knot selection algorithm offers a superior alternative to standard methods for RCS regression in epidemiology.
  • The 'knutar' R-package provides a practical tool for researchers to implement this improved knot selection technique.
  • This method enhances the reliability and generalizability of epidemiological models employing non-linear relationships.