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

Search research articles

Related Experiment Videos

[Roaming through methodology. XVI. What to do about missing data].

T Stijnen¹, L R Arends

¹Erasmus Universiteit, faculteit Geneeskunde en Gezondheidsweten-schappen, Instituut Epidemiologie en Biostatistiek, Rotterdam. stijnen@epib.fgg.eur

Nederlands Tijdschrift Voor Geneeskunde

|October 27, 1999

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

Describing fluctuating indoor aerosol dust measurements with application to house dust mite allergens.

Scientific reports·2020

Same author

Epidural volume extension - a reply.

Anaesthesia·2018

Same author

Effects of epidural volume extension by saline injection on the efficacy and safety of intrathecal local anaesthetics: systematic review with meta-analysis, meta-regression and trial sequential analysis.

Anaesthesia·2017

Same author

Frequency of submicroscopic chromosomal aberrations in pregnancies without increased risk for structural chromosomal aberrations: systematic review and meta-analysis.

Ultrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology·2017

Same author

Safety of Anti-TNF Treatment in Liver Transplant Recipients: A Systematic Review and Meta-analysis.

Journal of Crohn's & colitis·2017

Same author

Suicidal ideation and subsequent completed suicide in both psychiatric and non-psychiatric populations: a meta-analysis.

Epidemiology and psychiatric sciences·2016

Same journal

[Insulin intoxications caused by falsified semaglutide].

Nederlands tijdschrift voor geneeskunde·2026

Same journal

[Professional skepticism in medical research].

Nederlands tijdschrift voor geneeskunde·2026

Same journal

[Improving mobility in painful osteoarthritis].

Nederlands tijdschrift voor geneeskunde·2026

Same journal

[The effectiveness and costs of the Back At work After Surgery (BAAS) work-integrated care pathway on return to work for patients receiving knee arthroplasty].

Nederlands tijdschrift voor geneeskunde·2026

Same journal

[The rise of genetic therapies: urgent moral and societal questions].

Nederlands tijdschrift voor geneeskunde·2026

Same journal

[A man with a wound on his elbow].

Nederlands tijdschrift voor geneeskunde·2026

See all related articles

Missing data in medical research can bias results. Advanced statistical methods like multiple imputation offer more reliable analysis than complete case analysis when data are missing at random.

Area of Science:

Biostatistics
Medical Research Methodology

Context:

Medical research frequently encounters missing data across multiple patient measurements.
Traditional methods like complete case analysis can introduce significant bias.
These methods rely on the strong assumption of data missing completely at random (MCAR).

Purpose:

To compare the validity of different statistical approaches for handling missing data in medical research.
To highlight the limitations of complete case analysis and the benefits of advanced methods.

Summary:

Missing data in patient studies pose analytical challenges.
Complete case analysis and analyzing all available data are prone to bias unless data are missing completely at random (MCAR).
Likelihood-based approaches and multiple imputation are valid under the less stringent missing at random (MAR) assumption, efficiently utilizing all available data.

Related Experiment Videos

Impact:

Promotes the use of more robust statistical methods for missing data.
Encourages researchers to consider the assumptions underlying their chosen analytical techniques.
Aims to improve the accuracy and reduce bias in medical research findings.