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Random error units, extension of a novel method to express random error in epidemiological studies
Imre Janszky1, Johan Håkon Bjørngaard1, Pål Romundstad1
1Deparment of Public Health, Faculty of Medicine and Health, Norwegian University of Science and Technology, Trondheim, Norway, imre.janszky@ntnu.no.
Clinical Epidemiology
|February 19, 2019
Summary
This study introduces Random Error Units (REU) to simplify quantifying random error in epidemiology. This accessible method avoids statistical misinterpretation and enhances the analysis of various association measures and continuous variables.
Area of Science:
- Epidemiology
- Biostatistics
Background:
- Current methods for expressing random error in biomedical research are frequently misinterpreted and misused.
- A previous proposal introduced Random Error Units (REU) for quantifying random error in epidemiological studies with binary exposures.
Purpose of the Study:
- To expand the application of REU to common epidemiological measures of association and continuous variables.
- To provide a user-friendly tool for calculating REU.
Main Methods:
- The study extends the REU concept to various measures of association.
- The approach is applied to continuous variables.
- A Stata program was developed to facilitate REU calculation.
Main Results:
- The REU method provides a clear and interpretable way to quantify random error.
- The developed Stata program simplifies the calculation of REU for broader use.
- The expanded application allows for more robust analysis of epidemiological data.
Conclusions:
- The REU method offers an accessible and less prone to misinterpretation approach to quantifying random error in epidemiology.
- The availability of a Stata program promotes wider adoption and accurate application of REU in research.
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