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

Stratified Sampling Method01:16

Stratified Sampling Method

Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. The sampling method ensures that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a stratified sample, divide the population into groups called strata and then take a...
Spearman's Rank Correlation Test01:20

Spearman's Rank Correlation Test

Spearman's rank correlation test, also known as Spearman's rho, is a nonparametric method for assessing the strength and direction of association between two variables. This test is particularly valuable when the data distribution is unknown or when the assumption of normality does not hold. Named after the English psychologist and statistician Dr. Charles Edward Spearman, it serves as the nonparametric counterpart to Pearson's correlation coefficient.
Spearman's test calculates correlation by...
Strategies for Assessing and Addressing Confounding01:25

Strategies for Assessing and Addressing Confounding

Confounding is a critical issue in epidemiological studies, often leading to misleading conclusions about associations between exposures and outcomes. It occurs when the relationship between the exposure and the outcome is mixed with the effects of other factors that influence the outcome. Given that, addressing confounding is of high importance for drawing accurate inferences in research.
Confounding can be addressed at both the design phase of a study and through analytical methods after data...
Ranks01:02

Ranks

Unlike parametric methods, nonparametric statistics are ideal for nominal and ordinal data, requiring fewer assumptions about the population's nature or distribution. This makes nonparametric methods easier to apply and interpret, as they do not depend on parameters like mean or standard deviation. One common approach in nonparametric analysis is to sort data according to a specific criterion. For instance, we might arrange weather data from hottest to coldest days in a month or rank cities...
Principal Stresses: Problem Solving01:15

Principal Stresses: Problem Solving

When analyzing two planes intersecting at right angles under the influence of shearing, tensile, and compressive stresses, it is essential to identify principal planes, maximum shearing stress, and principal stresses. To find the principal planes, apply a formula that equates them to twice the shearing stress divided by the difference between tensile and compressive stresses.
Friedman Two-way Analysis of Variance by Ranks01:21

Friedman Two-way Analysis of Variance by Ranks

Friedman's Two-Way Analysis of Variance by Ranks is a nonparametric test designed to identify differences across multiple test attempts when traditional assumptions of normality and equal variances do not apply. Unlike conventional ANOVA, which requires normally distributed data with equal variances, Friedman's test is ideal for ordinal or non-normally distributed data, making it particularly useful for analyzing dependent samples, such as matched subjects over time or repeated measures from...

You might also read

Related Articles

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

Sort by
Same author

Regression-based Modeling of Spearman's Rho for Longitudinal Metabolomics and Mental Wellness in Breast Cancer Patients.

bioRxiv : the preprint server for biology·2026
Same author

HIV-related tuberculosis: mortality risk in persons without vs. with culture-confirmed disease.

The international journal of tuberculosis and lung disease : the official journal of the International Union against Tuberculosis and Lung Disease·2019
Same author

Current Practices in Choosing Estimands and Sensitivity Analyses in Clinical Trials: Results of the ICH E9 Survey.

Therapeutic innovation & regulatory science·2018
Same author

Older age at first tuberculosis diagnosis is associated with tuberculosis recurrence in HIV-negative persons.

The international journal of tuberculosis and lung disease : the official journal of the International Union against Tuberculosis and Lung Disease·2018
Same author

Trends in proportion of older HIV-infected people in care in Latin America and the Caribbean: a growing challenge.

Epidemiology and infection·2018
Same author

Outcomes of HIV-positive patients with cryptococcal meningitis in the Americas.

International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases·2017
Same journal

Interpretable Bayesian Modeling for Multireader Multicase Studies: Addressing Overdispersion and Limited Sample Size in Diagnostic Enhancement Evaluation.

Statistics in medicine·2026
Same journal

Adaptive Sequential Multiple Hypotheses Testing for Concomitant Vaccine Safety Surveillance.

Statistics in medicine·2026
Same journal

Novel Distance Regression for Repeated Outcomes With Missing Data: Applications to Longitudinal and Crossover Studies of Microbiome Beta-Diversity.

Statistics in medicine·2026
Same journal

Optimal Weighted Tests for Replication Studies and the 'Two-Trials Rule' With Multiple Hypotheses.

Statistics in medicine·2026
Same journal

Identifiable Copula-Double-Cox Models: A Fully Parametric Framework for Dependent Right-Censored Survival Data.

Statistics in medicine·2026
Same journal

Moving From Individualized Risk-Based Prevention to Benefit-Based Prevention: Estimating Individualized Life-Years Gained From Prevention Services as a Basis for Eligibility.

Statistics in medicine·2026
See all related articles

Related Experiment Video

Updated: May 11, 2026

Assessment of Spatial Lingual Tactile Sensitivity using a Gratings Orientation Test
06:00

Assessment of Spatial Lingual Tactile Sensitivity using a Gratings Orientation Test

Published on: September 17, 2021

Rank-based principal stratum sensitivity analyses.

X Lu1, D V Mehrotra, B E Shepherd

  • 1Department of Biostatistics, University of Florida, Gainesville, FL, 32610, U.S.A.

Statistics in Medicine
|May 21, 2013
PubMed
Summary
This summary is machine-generated.

This study introduces rank-based methods to analyze treatment effects in specific subgroups, offering sensitivity analyses for improved statistical rigor in clinical trials. The findings guide the application of these novel statistical approaches in real-world studies.

Keywords:
causal inferencemonotonicitynon-normalityprincipal stratificationranks

Related Experiment Videos

Last Updated: May 11, 2026

Assessment of Spatial Lingual Tactile Sensitivity using a Gratings Orientation Test
06:00

Assessment of Spatial Lingual Tactile Sensitivity using a Gratings Orientation Test

Published on: September 17, 2021

Area of Science:

  • Biostatistics
  • Clinical Trials Methodology
  • Statistical Sensitivity Analysis

Background:

  • Principal stratification is crucial for analyzing treatment effects when outcomes are subgroup-dependent.
  • Existing methods may lack robustness when outcomes are only defined post-randomization within specific subgroups.
  • Sensitivity analyses are vital for assessing the impact of unobserved confounders or model assumptions.

Purpose of the Study:

  • To develop and evaluate rank-based statistical methods for estimating principal stratification treatment effects.
  • To conduct sensitivity analyses by systematically varying key parameters.
  • To provide recommendations for applying these methods in complex clinical trial settings.

Main Methods:

  • Development of three novel rank-based test statistics for principal stratification.
  • Performance evaluation through extensive simulations.
  • Investigation of three bootstrap approaches for significance testing.
  • Application to real-world data from an HIV vaccine trial and a prostate cancer prevention trial.

Main Results:

  • The study presents comparative performance metrics for the proposed rank-based statistics.
  • Simulation results inform the selection of appropriate methods under different scenarios.
  • Bootstrap approaches demonstrate feasibility for determining statistical significance.
  • Successful application to diverse clinical trial contexts validates the methods' utility.

Conclusions:

  • Rank-based sensitivity analyses provide a robust framework for principal stratification treatment effects.
  • The proposed methods enhance statistical rigor in studies with post-randomization subgroup outcome definitions.
  • Recommendations are provided for practical implementation in HIV and prostate cancer research.