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

Test for Homogeneity01:23

Test for Homogeneity

1.9K
The goodness–of–fit test can be used to decide whether a population fits a given distribution, but it will not suffice to decide whether two populations follow the same unknown distribution. A different test, called the test for homogeneity, can be used to conclude whether two populations have the same distribution. To calculate the test statistic for a test for homogeneity, follow the same procedure as with the test of independence. The hypotheses for the test for homogeneity can...
1.9K
One-Way ANOVA: Equal Sample Sizes01:15

One-Way ANOVA: Equal Sample Sizes

3.2K
One-Way ANOVA can be performed on three or more samples with equal or unequal sample sizes. When one-way ANOVA is performed on two datasets with samples of equal sizes, it can be easily observed that the computed F statistic is highly sensitive to the sample mean.
Different sample means can result in different values for the variance estimate: variance between samples. This is because the variance between samples is calculated as the product of the sample size and the variance between the...
3.2K
Teeth01:15

Teeth

290
The formation of teeth, also known as odontogenesis, is a complex process that begins in utero, around the sixth week of embryonic development. There are three stages to this process: the bud stage, the cap stage, and the bell stage.
In the bud stage, the tooth germ (an aggregation of cells) starts to form in the developing jawbone. During the cap stage, the tooth germ differentiates into enamel organ, dental papilla, and dental sac, which will later develop into the tooth's enamel, dentin...
290
Chi-square Analysis02:46

Chi-square Analysis

37.1K
The chi-square test is a statistical hypothesis test. It is used to check whether there is a significant difference between an expected value and an observed value. In the context of genetics, it enables us to either accept or reject a hypothesis, based on how much the observed values deviate from the expected values.
The chi-square test was developed by Pearson in 1990.
The first step of performing a Chi-square analysis is to establish a null hypothesis, which assumes that there is no real...
37.1K
One-Way ANOVA: Unequal Sample Sizes01:15

One-Way ANOVA: Unequal Sample Sizes

5.7K
One-way ANOVA can be performed on three or more samples of unequal sizes. However, calculations get complicated when sample sizes are not always the same. So, while performing ANOVA with unequal samples size, the following equation is used:
5.7K
Regression Toward the Mean01:52

Regression Toward the Mean

6.3K
Regression toward the mean (“RTM”) is a phenomenon in which extremely high or low values—for example, and individual’s blood pressure at a particular moment—appear closer to a group’s average upon remeasuring. Although this statistical peculiarity is the result of random error and chance, it has been problematic across various medical, scientific, financial and psychological applications. In particular, RTM, if not taken into account, can interfere when...
6.3K

You might also read

Related Articles

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

Sort by
Same author

Third molar agenesis: An updated systematic review and meta-analysis.

Archives of oral biology·2026
Same author

Transition from independent midwifery care to Early Prevention Network Services in Germany - a cross-sectional survey.

BMC health services research·2026
Same author

Reporting of Animal Studies on Craniofacial Bone Repair: 2004, 2014, and 2024.

Journal of dental research·2026
Same author

Inconsistency was more prevalent than reported: an empirical study of 57 networks with multiple treatments using the node-splitting approach and a novel interpretation index.

Systematic reviews·2025
Same author

Transcription Accuracy of Automatic Speech Recognition for Orthodontic Clinical Records.

Journal of dental research·2025
Same author

Factors Affecting the Efficacy of Airflowing in Cleaning Implant Surfaces in a Surgical Peri-Implantitis Treatment Simulation-A Laboratory Study.

Clinical oral implants research·2025
Same journal

<i>Porphyromonas gingivalis</i>-Induced NETs Mediate Neuroinflammation via TLR4 Activation.

Journal of dental research·2026
Same journal

Oral Burden of Sjögren Disease: A Systematic Review and Meta-analysis.

Journal of dental research·2026
Same journal

Gingival Fibroblast-Driven Osteoimmunology via the IL-33-ILC2-IL-13 Axis.

Journal of dental research·2026
Same journal

Advancing a Global Oral Health Research Agenda.

Journal of dental research·2026
Same journal

YAP/TAZ Drive Oral Leukoplakia Progression and Confer Ferroptosis Vulnerability.

Journal of dental research·2026
Same journal

Multiancestral GWAS of Dental Malocclusion Identifies Multiple Risk Loci.

Journal of dental research·2026
See all related articles

Related Experiment Video

Updated: May 27, 2025

Oral Health Assessment by Lay Personnel for Older Adults
08:47

Oral Health Assessment by Lay Personnel for Older Adults

Published on: February 2, 2020

12.6K

Statistical Heterogeneity in Oral Health Meta-Analyses.

Z Tatas1, E Kyriakou2, J Seehra3

  • 1Department of Orthodontics and Dentofacial Orthopedics, Dental School/Medical Faculty, University of Bern, Bern, Switzerland.

Journal of Dental Research
|February 17, 2025
PubMed
Summary
This summary is machine-generated.

Oral health meta-analyses frequently over-rely on the I² statistic for interpreting statistical heterogeneity and selecting models. This overreliance on I² can lead to flawed conclusions in systematic reviews.

Keywords:
I2dental healthmeta-analysissystematic reviewsuncertaintyτ2

More Related Videos

Oral Biofilm Sampling for Microbiome Analysis in Healthy Children
10:42

Oral Biofilm Sampling for Microbiome Analysis in Healthy Children

Published on: December 31, 2017

17.0K
Precision of In Vivo Quantitative Tooth Wear Measurement Using Intra-Oral Scans
09:10

Precision of In Vivo Quantitative Tooth Wear Measurement Using Intra-Oral Scans

Published on: July 12, 2022

2.8K

Related Experiment Videos

Last Updated: May 27, 2025

Oral Health Assessment by Lay Personnel for Older Adults
08:47

Oral Health Assessment by Lay Personnel for Older Adults

Published on: February 2, 2020

12.6K
Oral Biofilm Sampling for Microbiome Analysis in Healthy Children
10:42

Oral Biofilm Sampling for Microbiome Analysis in Healthy Children

Published on: December 31, 2017

17.0K
Precision of In Vivo Quantitative Tooth Wear Measurement Using Intra-Oral Scans
09:10

Precision of In Vivo Quantitative Tooth Wear Measurement Using Intra-Oral Scans

Published on: July 12, 2022

2.8K

Area of Science:

  • Biostatistics
  • Dental Research
  • Evidence-Based Dentistry

Background:

  • Good meta-analysis reporting includes effect size, uncertainty, prediction intervals, and statistical heterogeneity measures.
  • Common heterogeneity measures are tau-squared (τ²) and I² statistics.
  • Over-reliance on I² can lead to misuse of meta-analysis models and reporting deficiencies.

Purpose of the Study:

  • To empirically assess the reporting and interpretation of statistical heterogeneity in oral health systematic reviews.
  • To investigate the selection of meta-analysis models based on heterogeneity measures.

Main Methods:

  • Systematic review of meta-analyses in oral health published 2021-2023 across 21 dental journals.
  • Extraction of characteristics at systematic review and meta-analysis levels.
  • Analysis of 313 systematic reviews with meta-analyses.

Main Results:

  • Random-effects models were prevalent (89%).
  • I² was reported in 98% of meta-analyses, while τ² was reported in 51%.
  • Most meta-analyses (96%) based heterogeneity interpretation on I², and 42% selected models based on I².

Conclusions:

  • Oral health meta-analyses demonstrate an overreliance on the I² statistic for heterogeneity interpretation and model selection.
  • Inappropriate use of I² may compromise the quality of conclusions in systematic reviews.
  • Further guidance on appropriate use of heterogeneity measures is warranted.