Confidence Intervals and Power Calculations for Within-Person Biological Variation: Effect of Analytical Imprecision, Number of Replicates, Number of Samples, and Number of Individuals

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Abstract
BACKGROUND: Reliable estimates of within-person biological variation and reference change value are of great importance when interpreting test results, monitoring patients, and setting quality specifications. Little information has been published regarding what experimental design is optimal to achieve the best estimates of within-person biological variation. METHOD: Expected CIs were calculated for different balanced designs for a 2-level nested variance analysis model with varying analytical imprecision. We also simulated data sets based on the model to calculate the power of different study designs for detection of within-person biological variation. RESULTS: The reliability of an estimate for biological variation and a study's power is very much influenced by the study design and by the ratio between analytical imprecision and within-person biological variation. For a fixed number of measurements, it is preferable to have a high number of samples from each individual. Shortcomings in analytical imprecision can be controlled by increasing the number of replicates. CONCLUSIONS: The design of an experiment to estimate biological variation should take into account the analytical imprecision of the method and focus on obtaining the highest possible reliability. Estimates of biological variation should always be reported with CIs.

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