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 Experiment Videos

A local influence sensitivity analysis for incomplete longitudinal depression data.

Shuyi Shen1, Caroline Beunckens, Craig Mallinckrodt

  • 1Eli Lilly & Company, Indianapolis, Indiana, USA.

Journal of Biopharmaceutical Statistics
|May 27, 2006
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

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

Sort by
Same author

Evaluation of surrogate endpoints for survival outcomes using the surrogate package in R.

Computer methods and programs in biomedicine·2026
Same author

Integrating oral health screening into general practice: validation study of the Oral Health Screener.

Scientific reports·2026
Same author

Multifunctional Piezoelectric Foams Enabling Noise Absorption and Deep-Learning-Driven Motion Recognition.

Small (Weinheim an der Bergstrasse, Germany)·2026
Same author

Time-Scale Target Parameters and Two-Step Estimation in Longitudinal Trials for Progressive Diseases.

Statistics in medicine·2026
Same author

Clinical outcomes and Th17-associated immunomodulation in vitiligo treated with tacrolimus ointment plus narrow-band ultraviolet light.

Pakistan journal of pharmaceutical sciences·2026
Same author

First investigation into occurrence, trophodynamics, and risk implication of polychlorinated naphthalenes and polychlorinated biphenyls in a terrestrial food chain from Tibetan Plateau.

Environmental pollution (Barking, Essex : 1987)·2026
Same journal

Correction.

Journal of biopharmaceutical statistics·2026
Same journal

Leveraging external controls in clinical trials: estimands, estimation, assumptions.

Journal of biopharmaceutical statistics·2026
Same journal

Special issue of nonclinical statistics in regulatory applications guest editors' notes.

Journal of biopharmaceutical statistics·2026
Same journal

Comparison of flexible parametric modeling and nonparametric methods to estimate restricted mean survival time: A simulation study.

Journal of biopharmaceutical statistics·2026
Same journal

Simulated treatment comparisons with jackknife pseudo values for estimating population-adjusted marginal treatment effects.

Journal of biopharmaceutical statistics·2026
Same journal

Sample sizes for randomized controlled trials utilizing Bayesian response adaptive randomization for continuous outcomes.

Journal of biopharmaceutical statistics·2026
See all related articles

This study advocates for sensitivity analyses in clinical trials with incomplete data. It suggests assessing results

Area of Science:

  • Biostatistics
  • Clinical Trials
  • Longitudinal Data Analysis

Background:

  • Traditional methods for incomplete longitudinal clinical trial data often assume data are missing completely at random (MCAR).
  • A shift towards principled ignorable analyses (likelihood-based or Bayesian) is occurring, valid under the less restrictive missing at random (MAR) assumption.
  • Standard statistical software now supports these advanced analytical approaches in practice.

Purpose of the Study:

  • To evaluate the utility of sensitivity analyses for incomplete longitudinal clinical trial data.
  • To demonstrate the application of the local influence sensitivity tool in a real-world clinical trial setting.
  • To assess the robustness of primary analyses against potential departures from the MAR assumption.

Main Methods:

Related Experiment Videos

  • Utilized likelihood-based and Bayesian ignorable analysis methods.
  • Employed the local influence sensitivity tool (Verbeke et al., 2001) for sensitivity analysis.
  • Applied these methods to continuous outcomes from a longitudinal depression clinical trial.

Main Results:

  • Ignorable analyses offer a more robust approach than simple ad hoc methods for incomplete data.
  • Sensitivity analyses are crucial for understanding the impact of potential deviations from the MAR assumption.
  • The local influence tool effectively assesses the sensitivity of trial results to missing data patterns and influential observations.

Conclusions:

  • Analyses valid under the missing not at random (MNAR) assumption are not ideal for primary clinical trial analysis.
  • Sensitivity analyses provide a valuable context for evaluating the impact of MNAR scenarios and influential data points.
  • The local influence approach is a practical tool for enhancing the reliability of findings from longitudinal clinical trials with incomplete data.