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Related Experiment Video

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An R-Based Landscape Validation of a Competing Risk Model

An R-Based Landscape Validation of a Competing Risk Model

Published on: September 16, 2022

From floated to conventional confidence intervals for the relative risks based on published dose-response data.

Nicola Orsini¹

¹Karolinska Institutet, National Institute of Environmental Medicine, Nobelsvag 13, 17155 Stockholm, Sweden. nicola.orsini@ki.se

Computer Methods and Programs in Biomedicine

|December 5, 2009

Summary

This study explains how to convert floated confidence intervals to conventional ones for meta-analysis. A Stata program is provided to help researchers accurately analyze epidemiological data, such as alcohol intake and cancer risk.

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Area of Science:

Epidemiology
Biostatistics
Medical Research

Background:

Dose-response meta-analyses often present confidence intervals (CIs) in varied formats (floated vs. conventional).
Inconsistent CI reporting complicates the accurate synthesis of evidence from epidemiological studies.

Purpose of the Study:

To provide a method for back-calculating conventional confidence intervals from floated confidence intervals or standard errors.
To develop and offer a user-friendly Stata program for implementing these calculations.

Main Methods:

The study details the mathematical formulas required to convert floated CIs to conventional CIs.
A practical application using published data on alcohol consumption and endometrial cancer risk is demonstrated.

Main Results:

The proposed method allows for the accurate conversion of different CI formats encountered in meta-analyses.
The Stata program facilitates straightforward application of these statistical techniques.

Conclusions:

Accurate calculation and reporting of confidence intervals are crucial for reliable meta-analysis results.
The developed tool enhances the ability of researchers to perform robust dose-response meta-analyses, improving the interpretation of epidemiological findings.