RE (Relative bias in percent)
Relative bias, also known as undercoverage bias when expressed relatively, offers a means to evaluate the magnitude of bias attributed to undercoverage concerning the true, yet unknown parameter that requires estimation. It allows for an assessment of the discrepancy between the estimated parameter and the actual parameter, considering the inherent bias caused by undercoverage.
Expressing bias relative to its true value enables a clearer understanding of the extent to which undercoverage impacts the estimation process. By dividing the bias value by 100, it is feasible to obtain the relative bias, providing a standardized measure of the bias compared to the true parameter. This normalization process aids in quantifying the relative impact of undercoverage bias on the estimation procedure.
In essence, relative bias serves as a valuable metric in assessing the accuracy and reliability of estimations, particularly in scenarios where undercoverage is a prevalent concern. By quantifying bias relative to the true parameter, analysts and researchers gain insights into the extent of deviation from the actual value, thus facilitating informed decision-making and refinement of estimation methodologies.
Where Oi is the observation value and Pi is the forecast value.
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Related Question: What does bias mean?
Please provide the data in a two-column format (observed vs. simulated). You can copy from Excel, text, or any other format, separated by space.
Relative bias in percent: %