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

Study Designs in Epidemiology01:20

Study Designs in Epidemiology

778
Epidemiological study designs are fundamental tools for investigating the distribution, determinants, and control of health conditions in populations. They help researchers understand the relationships between exposures and outcomes, and they broadly fall into two categories: "observational" and "experimental" studies.
Observational studies are those where the researcher does not intervene but rather observes natural variations. They include cross-sectional, cohort, and...
778
Bias in Epidemiological Studies01:29

Bias in Epidemiological Studies

1.1K
Biases can arise at various stages of research, from study design and data collection to analysis and interpretation. Recognizing and addressing these biases is essential to ensure the validity and reliability of epidemiological findings.Broadly speaking, biases in epidemiology fall into three main categories: selection bias, information bias, and confounding. A more detailed description of possible biases is:  
1.1K
Statistical Methods for Analyzing Epidemiological Data01:25

Statistical Methods for Analyzing Epidemiological Data

817
Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:
817
Introduction to Epidemiology01:26

Introduction to Epidemiology

1.5K
Epidemiology, known as the cornerstone of public health, involves studying the distribution and determinants of health-related events in defined populations and applying these insights to control health issues. This is essential for understanding how diseases spread, identifying populations at greater risk, and implementing measures to control or prevent outbreaks. Epidemiology addresses not only infectious diseases but also non-communicable conditions like cancer and cardiovascular disease,...
1.5K
Strategies for Assessing and Addressing Confounding01:25

Strategies for Assessing and Addressing Confounding

298
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...
298
Confounding in Epidemiological Studies01:27

Confounding in Epidemiological Studies

503
Confounding in statistical epidemiology represents a pivotal challenge, referring to the distortion in the perceived relationship between an exposure and an outcome due to the presence of a third variable, known as a confounder. This variable is associated with both the exposure and the outcome but is not a direct link in their causal chain. Its presence can lead to erroneous interpretations of the exposure's effect, either exaggerating or underestimating the true association. This...
503

You might also read

Related Articles

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

Sort by
Same author

International survey on the management of IgA deficiency: The BEST Collaborative Study.

Vox sanguinis·2026
Same author

Blood donor safety and selection criteria for individuals self-identifying as trans or non-binary.

Vox sanguinis·2026
Same author

Chagas disease in Canadian blood donors: 15 years of selective testing.

Vox sanguinis·2026
Same author

Blood donor hepatitis B data: An under-recognized surveillance resource in Canada.

Canadian liver journal·2026
Same author

Treating maternal mental health problems with an app-based program: A randomized control trial of the Building Emotional Awareness and Mental Health (BEAM) program, for mothers of young children.

Journal of consulting and clinical psychology·2026
Same author

Testosterone, cortisol, and bullying perpetration in adolescents: The moderating role of peer victimization.

Development and psychopathology·2026
Same journal

Age at menarche and adverse pregnancy and perinatal outcomes: triangulating evidence from multivariable and Mendelian randomization analyses.

International journal of epidemiology·2026
Same journal

Life-course trajectories of cardiovascular disease risk factors in rural India: Andhra Pradesh Children and Parents Study (APCAPS) 2003-2023.

International journal of epidemiology·2026
Same journal

Cohort Profile Update: The Young Lives study.

International journal of epidemiology·2026
Same journal

From the departing Editors in Chief.

International journal of epidemiology·2026
Same journal

Data Resource Profile: Cheeloo Lifespan Electronic-health reseArch Data-library (Cheeloo LEAD).

International journal of epidemiology·2026
Same journal

Cohort Profile Update: The Swiss Childhood Cancer Survivor Cohort.

International journal of epidemiology·2026
See all related articles

Related Experiment Video

Updated: Dec 22, 2025

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

15.0K

Reflection on modern methods: planned missing data designs for epidemiological research.

Charlie Rioux1, Antoine Lewin2,3, Omolola A Odejimi1

  • 1Department of Educational Psychology and Leadership, College of Education, Texas Tech University, Lubbock, TX, USA.

International Journal of Epidemiology
|May 2, 2020
PubMed
Summary
This summary is machine-generated.

Planned missing data designs strategically incorporate missing data in epidemiological studies. These methods, including multiform and wave-missing designs, reduce costs and participant burden while maintaining data validity and statistical power.

Keywords:
Methodsbiasdata qualitymeasurementmissing dataquestionnaire designresearch design

More Related Videos

Visualizing Field Data Collection Procedures of Exposure and Biomarker Assessments for the Household Air Pollution Intervention Network Trial in India
09:33

Visualizing Field Data Collection Procedures of Exposure and Biomarker Assessments for the Household Air Pollution Intervention Network Trial in India

Published on: December 23, 2022

2.6K
Author Spotlight: Evaluating the Adjuvant Efficacy and Safety of Angong Niuhuang Pill in Viral Encephalitis Treatment
08:36

Author Spotlight: Evaluating the Adjuvant Efficacy and Safety of Angong Niuhuang Pill in Viral Encephalitis Treatment

Published on: April 19, 2024

1.0K

Related Experiment Videos

Last Updated: Dec 22, 2025

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

15.0K
Visualizing Field Data Collection Procedures of Exposure and Biomarker Assessments for the Household Air Pollution Intervention Network Trial in India
09:33

Visualizing Field Data Collection Procedures of Exposure and Biomarker Assessments for the Household Air Pollution Intervention Network Trial in India

Published on: December 23, 2022

2.6K
Author Spotlight: Evaluating the Adjuvant Efficacy and Safety of Angong Niuhuang Pill in Viral Encephalitis Treatment
08:36

Author Spotlight: Evaluating the Adjuvant Efficacy and Safety of Angong Niuhuang Pill in Viral Encephalitis Treatment

Published on: April 19, 2024

1.0K

Area of Science:

  • Epidemiology
  • Biostatistics

Background:

  • Modern missing data treatments, like multiple imputation, can handle missing data without bias.
  • Planned missing data designs leverage these methods by intentionally introducing missingness.

Purpose of the Study:

  • To describe planned missing data designs in epidemiological research.
  • To outline the benefits, impact on bias and power, and implementation considerations for these designs.

Main Methods:

  • Description of three planned missing data designs: multiform, wave-missing, and two-method.
  • Discussion of how these designs interact with modern missing data treatments.

Main Results:

  • Planned missing data designs can minimize data collection costs and reduce participant burden.
  • These designs can increase overall study validity and statistical power when implemented correctly.

Conclusions:

  • Planned missing data designs offer a strategic approach to enhance epidemiological research efficiency and validity.
  • Methodological considerations are crucial for successful implementation in study design.