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

Censoring Survival Data01:09

Censoring Survival Data

82
Survival analysis is a statistical method used to analyze time-to-event data, often employed in fields such as medicine, engineering, and social sciences. One of the key challenges in survival analysis is dealing with incomplete data, a phenomenon known as "censoring." Censoring occurs when the event of interest (such as death, relapse, or system failure) has not occurred for some individuals by the end of the study period or is otherwise unobservable, and it might have many different...
82
Archival Research01:40

Archival Research

16.0K
Some researchers gain access to large amounts of data without interacting with a single research participant. Instead, they use existing records to answer various research questions. This type of research approach is known as archival research. Archival research relies on looking at past records or data sets to look for interesting patterns or relationships. For example, a researcher might access the academic records of all individuals who enrolled in college within the past ten years and...
16.0K
Longitudinal Research02:20

Longitudinal Research

12.0K
Sometimes we want to see how people change over time, as in studies of human development and lifespan. When we test the same group of individuals repeatedly over an extended period of time, we are conducting longitudinal research. Longitudinal research is a research design in which data-gathering is administered repeatedly over an extended period of time. For example, we may survey a group of individuals about their dietary habits at age 20, retest them a decade later at age 30, and then again...
12.0K
Sample Handling01:02

Sample Handling

100
Transportation of samples from the collection point to the laboratory, as well as storage and preservation techniques, are crucial for maintaining sample integrity and ensuring accurate and reliable test results.
Samples should be transported carefully from collection points to the laboratory. They should be properly sealed and clearly labeled to prevent cross-contamination. To preserve the sample integrity, optimal temperature conditions during transport are essential. This could involve using...
100
Ethics in Research01:56

Ethics in Research

23.0K
Today, scientists agree that good research is ethical in nature and is guided by a basic respect for human dignity and safety. However, this has not always been the case. Modern researchers must demonstrate that the research they perform is ethically sound.
23.0K
Detection of Gross Error: The Q Test01:00

Detection of Gross Error: The Q Test

6.1K
When one or more data points appear far from the rest of the data, there is a need to determine whether they are outliers and whether they should be eliminated from the data set to ensure an accurate representation of the measured value. In many cases, outliers arise from gross errors (or human errors) and do not accurately reflect the underlying phenomenon. In some cases, however, these apparent outliers reflect true phenomenological differences. In these cases, we can use statistical methods...
6.1K

You might also read

Related Articles

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

Sort by
Same authorSame journal

Qualitative research - Part 1.

Perspectives in clinical research·2026
Same author

Patient and public involvement in cancer care and research: the Indian perspective.

Ecancermedicalscience·2026
Same author

Addressing low-value care (LVC) in Asia: a narrative review of Choosing Wisely and other initiatives across Asia.

BMJ open quality·2026
Same author

Enhancing, controlling, and sterilizing dengue immunity and the development of broadly protective responses.

medRxiv : the preprint server for health sciences·2026
Same author

COVID-19 vaccine immunogenicity in Mongolian adults with and without chronic hepatitis.

BMC infectious diseases·2026
Same author

Assessment of the impact of a structured training program on knowledge of research methodology among anesthesiology trainees at a tertiary referral cancer center.

Perspectives in clinical research·2026
Same journal

Cross-tool evaluation of artificial intelligence-drafted informed consent documents: A 3-level study.

Perspectives in clinical research·2026
Same journal

Preparing for central drugs standard control organization ethics committee inspections in India: A review of regulatory expectations and readiness strategies.

Perspectives in clinical research·2026
Same journal

Competencies and operations of research ethics committee members and the protection of research participants: A scoping review.

Perspectives in clinical research·2026
Same journal

The Consolidated Standards of Reporting Trials Statement-2025: New epoch for improving the transparency of randomized trials reporting.

Perspectives in clinical research·2026
Same journal

Cost analysis and drug utilization pattern in diabetic patients attending outpatient at tertiary care teaching hospital in South Gujarat.

Perspectives in clinical research·2026
See all related articles

Related Experiment Video

Updated: Jun 26, 2025

Meta-analysis of Voxel-Based Neuroimaging Studies using Seed-based d Mapping with Permutation of Subject Images SDM-PSI
06:26

Meta-analysis of Voxel-Based Neuroimaging Studies using Seed-based d Mapping with Permutation of Subject Images SDM-PSI

Published on: November 27, 2019

70.6K

Handling missing data in research.

Priya Ranganathan1, Sally Hunsberger2

  • 1Department of Anaesthesiology, Tata Memorial Centre, Homi Bhabha National Institute, Mumbai, Maharashtra, India.

Perspectives in Clinical Research
|May 20, 2024
PubMed
Summary
This summary is machine-generated.

Missing data in research reduces sample size and can bias results. This article covers types of missing data, handling methods, and minimization strategies for more reliable study outcomes.

Keywords:
Data collectionimputationmissing data

More Related Videos

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index
06:55

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index

Published on: January 8, 2020

14.5K
Nest Building Behavior as an Early Indicator of Behavioral Deficits in Mice
06:11

Nest Building Behavior as an Early Indicator of Behavioral Deficits in Mice

Published on: October 19, 2019

19.8K

Related Experiment Videos

Last Updated: Jun 26, 2025

Meta-analysis of Voxel-Based Neuroimaging Studies using Seed-based d Mapping with Permutation of Subject Images SDM-PSI
06:26

Meta-analysis of Voxel-Based Neuroimaging Studies using Seed-based d Mapping with Permutation of Subject Images SDM-PSI

Published on: November 27, 2019

70.6K
Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index
06:55

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index

Published on: January 8, 2020

14.5K
Nest Building Behavior as an Early Indicator of Behavioral Deficits in Mice
06:11

Nest Building Behavior as an Early Indicator of Behavioral Deficits in Mice

Published on: October 19, 2019

19.8K

Area of Science:

  • Biostatistics
  • Research Methodology
  • Data Science

Background:

  • Missing data is a common challenge in research.
  • It can lead to reduced statistical power and biased findings.
  • Addressing missing data is crucial for research integrity.

Purpose of the Study:

  • To review different types of missing data.
  • To discuss methods for handling missing data.
  • To provide recommendations for minimizing missing data in future studies.

Main Methods:

  • Literature review of statistical approaches.
  • Categorization of missing data types (e.g., MCAR, MAR, MNAR).
  • Overview of imputation techniques and deletion methods.

Main Results:

  • Identified various sources and patterns of missing data.
  • Summarized the pros and cons of different data handling techniques.
  • Highlighted the impact of missing data on study generalizability.

Conclusions:

  • Effective handling of missing data is essential for valid research.
  • Choosing the appropriate method depends on the data and research question.
  • Proactive strategies can minimize the occurrence of missing data.