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

Statistical Methods for Analyzing Epidemiological Data01:25

Statistical Methods for Analyzing Epidemiological Data

366
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:
366
Statistical Methods to Analyze Parametric Data: ANOVA01:12

Statistical Methods to Analyze Parametric Data: ANOVA

374
Analysis of Variance, or ANOVA, is a powerful statistical technique used to analyze parametric data, primarily in research and experimental studies. It's designed to compare the means of two or more groups, assisting researchers in identifying any significant differences between these group means. There are two main types of ANOVA based on the complexity of the analysis: one-way and two-way.
One-way ANOVA is applied when a single independent variable or factor is scrutinized. It compares...
374
Statistical Software for Data Analysis and Clinical Trials01:12

Statistical Software for Data Analysis and Clinical Trials

554
Statistical software is pivotal in data analysis and clinical trials by providing tools to analyze data, draw conclusions, and make predictions. These software packages range from simple data management applications to complex analytical platforms, supporting various statistical tests, models, and simulation techniques. Their significance lies in their ability to handle vast amounts of data with precision and efficiency, enabling researchers to validate hypotheses, identify trends, and make...
554
Statistical Analysis System (SAS)01:14

Statistical Analysis System (SAS)

176
SAS, short for Statistical Analysis System, is a powerful data analysis, management, and visualization tool. Developed by the SAS Institute in the early 1970s, SAS has evolved into a comprehensive software suite used across various industries for statistical analysis, business intelligence, and predictive modeling.
Applications: SAS finds applications in numerous fields, including healthcare for clinical trial analysis, finance for risk assessment, marketing for customer data analysis, and...
176
Statistical Inference Techniques in Hypothesis Testing: Parametric Versus Nonparametric Data01:16

Statistical Inference Techniques in Hypothesis Testing: Parametric Versus Nonparametric Data

130
Statistical inference techniques, paramount in hypothesis testing, differentiate into two broad categories: parametric and nonparametric statistics.
Parametric statistics, as the name suggests, assumes that data follow a specific distribution, often a normal distribution. This assumption enables robust hypothesis testing and estimation. Parametric methods, like the Student's t-test or Goodness-of-fit test, are frequently employed in biostatistics due to their robustness. For instance,...
130
Parametric Survival Analysis: Weibull and Exponential Methods01:14

Parametric Survival Analysis: Weibull and Exponential Methods

436
Parametric survival analysis models survival data by assuming a specific probability distribution for the time until an event occurs. The Weibull and exponential distributions are two of the most commonly used methods in this context, due to their versatility and relatively straightforward application.
Weibull Distribution
The Weibull distribution is a flexible model used in parametric survival analysis. It can handle both increasing and decreasing hazard rates, depending on its shape parameter...
436

You might also read

Related Articles

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

Sort by
Same author

Primary Human Papillomavirus Screening Versus Cytology for Detection of Cervical Intraepithelial Neoplasia Grade 2 or Higher in Poland: a Parallel-Group, Randomized Controlled Trial.

The Lancet regional health. Europe·2026
Same author

Accuracy of colposcopy to triage HPV-positive women in cervical cancer screening: a systematic review and meta-analysis.

EClinicalMedicine·2026
Same author

Clinical Validation of the Roche cobas and cobas 4800 Human Papillomavirus Tests on Self-Collected Vaginal Dry Swabs versus Practitioner-Collected Cervical Specimens Using the VALHUDES Protocol.

The Journal of molecular diagnostics : JMD·2026
Same author

Resource-Adapted Triage Strategies for Women Testing HPV Positive With Self-Collected Vaginal Samples in Cameroon.

International journal of cancer·2026
Same author

Accuracy of Allplex HPV HR Detection Full Genotyping Assay on Cervical Samples Compared to Vaginal Self-Samples.

Journal of medical virology·2026
Same author

Diagnostic testing accuracy of DNA methylation tests for detection of high-grade cervical intraepithelial neoplasia and cervical cancer: A systematic review and meta-analysis.

European journal of cancer (Oxford, England : 1990)·2026

Related Experiment Video

Updated: Jul 4, 2025

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

526

Methods for meta-analysis and meta-regression of binomial data: concepts and tutorial with Stata command metapreg.

Victoria Nyawira Nyaga1, Marc Arbyn2

  • 1Unit of Cancer Epidemiology, Sciensano, Brussels, Belgium. victoria.nyawiranyaga@sciensano.be.

Archives of Public Health = Archives Belges De Sante Publique
|January 30, 2024
PubMed
Summary

metapreg offers advanced statistical methods for meta-analysis of binomial proportions, improving evidence synthesis. This Stata tool provides a robust alternative to traditional methods, enhancing the quality of meta-analysis results.

Keywords:
BinomialLogistic regressionMeta-analysisMeta-regressionNetwork meta-analysisStata

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
A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
10:46

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data

Published on: December 9, 2015

10.7K

Related Experiment Videos

Last Updated: Jul 4, 2025

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

526
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
A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
10:46

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data

Published on: December 9, 2015

10.7K

Area of Science:

  • Biostatistics
  • Statistical Modeling

Background:

  • Meta-analysis of proportions is widely used but conceptually challenging.
  • Current methods often rely on normal approximations, overlooking optimal generalized linear models.
  • A need exists for advanced statistical tools for robust meta-analysis of binomial data.

Purpose of the Study:

  • To introduce metapreg, a Stata tool for meta-analysis, network meta-analysis, and meta-regression of binomial proportions.
  • To elucidate the statistical rationale and models underpinning binomial proportion meta-analysis.
  • To compare metapreg's performance against existing methods through simulation.

Main Methods:

  • Development of metapreg in Stata utilizing binomial, logistic, and logistic-normal models.
  • Explanation of statistical concepts and models for binomial proportion meta-analysis.
  • Demonstration of metapreg using data from seven published meta-analyses.
  • Simulation study comparing metapreg estimators with metaprop and metan estimators.

Main Results:

  • metapreg provides a flexible and robust approach to evidence synthesis for binomial data.
  • The tool efficiently utilizes all available data without requiring continuity corrections or imputation.
  • Simulation results indicate competitive or superior performance of metapreg estimators.

Conclusions:

  • metapreg offers a rigorous and user-friendly tool for high-quality meta-analysis of binomial proportions.
  • The tool enhances the efficiency and accuracy of evidence synthesis.
  • Adoption of metapreg is expected to improve the overall quality of meta-analytic research on binomial data.