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

Receiver Operating Characteristic Plot01:15

Receiver Operating Characteristic Plot

A ROC (Receiver Operating Characteristic) plot is a graphical tool used to assess the performance of a binary classification model by illustrating the trade-off between sensitivity (true positive rate) and specificity (false positive rate). By plotting sensitivity against 1 - specificity across various threshold settings, the ROC curve shows how well the model distinguishes between classes, with a curve closer to the top-left corner indicating a more accurate model. The area under the ROC curve...
Area Problem01:26

Area Problem

Determining the area of a region with straight edges is straightforward, as geometric formulas for rectangles, triangles, and polygons can be applied directly. However, traditional geometric methods are insufficient when a region has a curved boundary, such as the area under a function.fromThe area problem involves finding a systematic way to measure such regions. One approach to solving this problem is through approximation. Instead of attempting to compute the area exactly at the outset, the...
Kaplan-Meier Approach01:24

Kaplan-Meier Approach

The Kaplan-Meier estimator is a non-parametric method used to estimate the survival function from time-to-event data. In medical research, it is frequently employed to measure the proportion of patients surviving for a certain period after treatment. This estimator is fundamental in analyzing time-to-event data, making it indispensable in clinical trials, epidemiological studies, and reliability engineering. By estimating survival probabilities, researchers can evaluate treatment effectiveness,...
Parametric Survival Analysis: Weibull and Exponential Methods01:14

Parametric Survival Analysis: Weibull and Exponential Methods

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...
Linear Approximation in Time Domain01:21

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...
Maxwell-Boltzmann Distribution: Problem Solving01:20

Maxwell-Boltzmann Distribution: Problem Solving

Individual molecules in a gas move in random directions, but a gas containing numerous molecules has a predictable distribution of molecular speeds, which is known as the Maxwell-Boltzmann distribution, f(v).
This distribution function f(v) is defined by saying that the expected number N (v1,v2) of particles with speeds between v1 and v2 is given by

You might also read

Related Articles

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

Sort by
Same author

Impact of intraoperative intravenous heparin bolus on clinical outcomes during radical nephrectomy and IVC tumor thrombectomy in renal cell carcinoma with level I-IV IVC thrombus: A multi-institutional study.

Urologic oncology·2026
Same author

Treatment-related outcomes and patterns of relapse in secondary CNS involvement by large B-cell lymphoma.

Blood·2026
Same author

A Tough Pill to Swallow: Bedside Dysphagia Screening in Geriatric Trauma Patients.

The Journal of surgical research·2025
Same author

Examining inpatient chemotherapy utilization among patients with cancer and impact on outcomes.

The oncologist·2025
Same author

A phase 1B trial of vocimagene amiretrorepvec in patients with advanced solid tumors: Safety, tumor homing, and immune modulatory effects.

Molecular therapy : the journal of the American Society of Gene Therapy·2025
Same author

Stimulating Soluble Guanylyl Cyclase with the Clinical Agonist Riociguat Restrains the Development and Progression of Castration-Resistant Prostate Cancer.

Cancer research·2024
Same journal

A Mixture of Distributed Lag Non-Linear Models to Account for Spatially Heterogeneous Exposure-Lag-Response Associations.

Statistics in medicine·2026
Same journal

Practical Considerations for Gaussian Process Modeling for Causal Inference in Quasi-Experimental Studies With Panel Data.

Statistics in medicine·2026
Same journal

Covariate Adjustment for Wilcoxon Two Sample Statistic and Test.

Statistics in medicine·2026
Same journal

Beyond Fixed Thresholds: Optimizing Summaries of Wearable Device Data via Piecewise Linearization of Quantile Functions.

Statistics in medicine·2026
Same journal

A Causal Framework for Evaluating the Total Effect of Strategies Aiming to Expand Screening and to Improve Outcomes.

Statistics in medicine·2026
Same journal

Causal Effects on Nonterminal Event Time With Application to Antibiotic Usage and Future Resistance.

Statistics in medicine·2026
See all related articles

Related Experiment Video

Updated: Jun 11, 2026

A Tactile Automated Passive-Finger Stimulator (TAPS)
19:44

A Tactile Automated Passive-Finger Stimulator (TAPS)

Published on: June 3, 2009

Simulation-Based Power Analysis for Time-Dependent Area Under Receiver Operating Characteristic Curve Using

Sunwoo Han1, Deukwoo Kwon2

  • 1Department of Biostatistics, Robert Stempel College of Public Health and Social Work, Florida International University, Miami, Florida, USA.

Statistics in Medicine
|June 10, 2026
PubMed
Summary
This summary is machine-generated.

This study introduces a simulation framework to analyze biomarker prognostic accuracy for time-to-event outcomes. It accurately estimates sample size, power, and effect size for clinical trial designs.

Keywords:
approximate Bayesian computationbiomarker assessmentpower analysissurvival analysistime‐dependent AUROC

More Related Videos

Effective Analysis of Human Exposure Conditions with Body-worn Dosimeters in the 2.4 GHz Band
06:43

Effective Analysis of Human Exposure Conditions with Body-worn Dosimeters in the 2.4 GHz Band

Published on: May 2, 2018

Continuous-Wave Propagation Channel-Sounding Measurement System - Testing, Verification, and Measurements
09:36

Continuous-Wave Propagation Channel-Sounding Measurement System - Testing, Verification, and Measurements

Published on: June 25, 2021

Related Experiment Videos

Last Updated: Jun 11, 2026

A Tactile Automated Passive-Finger Stimulator (TAPS)
19:44

A Tactile Automated Passive-Finger Stimulator (TAPS)

Published on: June 3, 2009

Effective Analysis of Human Exposure Conditions with Body-worn Dosimeters in the 2.4 GHz Band
06:43

Effective Analysis of Human Exposure Conditions with Body-worn Dosimeters in the 2.4 GHz Band

Published on: May 2, 2018

Continuous-Wave Propagation Channel-Sounding Measurement System - Testing, Verification, and Measurements
09:36

Continuous-Wave Propagation Channel-Sounding Measurement System - Testing, Verification, and Measurements

Published on: June 25, 2021

Area of Science:

  • Biostatistics
  • Clinical Trial Design
  • Biomarker Research

Background:

  • Assessing biomarker prognostic accuracy for time-to-event outcomes is crucial in clinical research.
  • Existing methods may not fully address complexities in study designs and biomarker types.

Purpose of the Study:

  • To propose a novel simulation-based power analysis framework for prognostic biomarker studies.
  • To enable accurate estimation of sample size, biomarker effect size, and statistical power.

Main Methods:

  • Developed a framework integrating Approximate Bayesian Computation (ABC) for pseudo-censored survival data generation.
  • Employed iterative Monte Carlo simulations for power and sample size estimation.
  • Accommodated single/staggered entry and continuous/dichotomized biomarkers.

Main Results:

  • Simulation studies confirmed the framework's accuracy and consistency across various designs.
  • Demonstrated reliable estimation of key statistical parameters.
  • Validated the approach with a real-world clinical trial in lymphoma.

Conclusions:

  • The proposed simulation framework offers a robust tool for designing prognostic biomarker studies.
  • It enhances the ability to plan and power clinical trials for time-to-event outcomes.
  • Facilitates more efficient and reliable biomarker evaluation in oncology and beyond.