
Currently used methods to express random error are often misinterpreted and consequently misused by biomedical researchers. Previously we proposed a simple approach to quantify the amount of random error in epidemiological studies using OR for binary exposures. Expressing random error with the number of random error units (REU) does not require solid background in statistics for a proper interpretation and cannot be misused for making oversimplistic interpretations relying on statistical significance. We now expand the use of REU to the most common measures of associations in epidemiology and to continuous variables, and we have developed a Stata program, which greatly facilitates the calculation of REU.
Methodology, Clinical Epidemiology, Infectious and parasitic diseases, RC109-216, p value, random error, confidence intervals
Methodology, Clinical Epidemiology, Infectious and parasitic diseases, RC109-216, p value, random error, confidence intervals
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