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

Steps in Outbreak Investigation01:18

Steps in Outbreak Investigation

405
In the ever-evolving field of public health, statistical analysis serves as a cornerstone for understanding and managing disease outbreaks. By leveraging various statistical tools, health professionals can predict potential outbreaks, analyze ongoing situations, and devise effective responses to mitigate impact. For that to happen, there are a few possible stages of the analysis:
405
Statistical Methods for Analyzing Epidemiological Data01:25

Statistical Methods for Analyzing Epidemiological Data

783
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:
783

You might also read

Related Articles

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

Sort by
Same author

Correction: AI-supported real-time news evaluation reveals effects of time constraint on misinformation discernment.

Scientific reports·2026
Same author

AI-supported real-time news evaluation reveals effects of time constraint on misinformation discernment.

Scientific reports·2026
Same author

Measuring the semantic priming effect across many languages.

Nature human behaviour·2025
Same author

The Relation Between the Public Attitude Towards COVID-19 and its Applied Policies - a Dataset for Binational and Temporal Comparison.

Journal of open psychology data·2025
Same author

Dropout analysis: A method for data from Internet-based research and dropR, an R-based web app and package to analyze and visualize dropout.

Behavior research methods·2025
Same author

Cross-cultural data on romantic love and mate preferences from 117,293 participants across 175 countries.

Scientific data·2025

Related Experiment Video

Updated: Dec 11, 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

70.7K

Meta-analysis in a digitalized world: A step-by-step primer.

Esther Kaufmann1, Ulf-Dietrich Reips2

  • 1Research Methods, Assessment, and iScience, Department of Psychology, University of Konstanz, Konstanz, Germany. esther.kaufmann@uni-konstanz.de.

Behavior Research Methods
|April 4, 2024
PubMed
Summary

This primer guides high-quality meta-analyses for digital research, recommending the Schmidt and Hunter approach. It addresses pitfalls in data aggregation and literature searches for improved quantitative estimations.

Keywords:
Digital researchInternet-based researchMega-analysisMeta-analysisOverviewResearch synthesis

More Related Videos

Comparing Bibliometric Analysis Using PubMed, Scopus, and Web of Science Databases
05:02

Comparing Bibliometric Analysis Using PubMed, Scopus, and Web of Science Databases

Published on: October 24, 2019

31.4K
Dynamic Digital Biomarkers of Motor and Cognitive Function in Parkinson's Disease
10:28

Dynamic Digital Biomarkers of Motor and Cognitive Function in Parkinson's Disease

Published on: July 24, 2019

15.2K

Related Experiment Videos

Last Updated: Dec 11, 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

70.7K
Comparing Bibliometric Analysis Using PubMed, Scopus, and Web of Science Databases
05:02

Comparing Bibliometric Analysis Using PubMed, Scopus, and Web of Science Databases

Published on: October 24, 2019

31.4K
Dynamic Digital Biomarkers of Motor and Cognitive Function in Parkinson's Disease
10:28

Dynamic Digital Biomarkers of Motor and Cognitive Function in Parkinson's Disease

Published on: July 24, 2019

15.2K

Area of Science:

  • Digital research methodologies
  • Quantitative synthesis
  • Meta-analysis techniques

Background:

  • Digitalization offers advantages for research, including comprehensive data collection and availability, ideal for meta-analyses.
  • Traditional lab research contrasts with the benefits of digital and Internet-based research approaches.
  • Various meta-analysis methods exist for accurate quantitative estimations in research synthesis.

Purpose of the Study:

  • To provide a step-by-step primer for conducting high-quality meta-analyses in a digitalized research environment.
  • To highlight common pitfalls in digital meta-analysis, including data aggregation, literature search, and coding.
  • To present the first mega meta-analysis of Internet-based research to identify research gaps.

Main Methods:

  • Recommending the Schmidt and Hunter approach for meta-analyses due to its correction capabilities in digitalized contexts.
  • Developing a primer detailing procedures for high-quality meta-analysis with digital data.
  • Conducting a mega meta-analysis synthesizing 15 articles on Internet-based research (745 studies, 1,601 effect sizes).

Main Results:

  • The Schmidt and Hunter approach is recommended for meta-analyses in the digital age.
  • A primer is provided to guide researchers in conducting and evaluating digital meta-analyses, addressing common pitfalls.
  • The mega meta-analysis revealed a lack of individual participant data (e.g., age, nationality) in Internet-based research.

Conclusions:

  • This primer offers essential knowledge for conducting and judging the quality of meta-analyses in the era of digital research.
  • The recommended methods and identified gaps are crucial for advancing quantitative synthesis in digitalized research environments.
  • Future meta-analyses should prioritize the inclusion of individual participant data to enhance research synthesis quality.