Background: In a planned International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) worldwide study on reference intervals (RIs), a common panel of serum samples is to be measured by laboratories from different countries, and test results are to be compared through conversion using linear regression analysis. This report presents a validation study that was conducted in collaboration with four laboratories. Methods: A panel composed of 80 sera was prepared from healthy individuals, and 45 commonly tested analytes (general chemistry, tumor markers, and hormones) were measured on two occasions 1 week apart in each laboratory. Reduced major-axis linear regression was used to convert reference limits ( LL and UL ). Precision was expressed as a ratio of the standard error of converted LL or UL to the standard deviation (SD) comprising RI (approx. 1/4 of the RI width corresponding to between-individual SD). The allowable and optimal levels of error for the SD ratio (SDR) were set as ≤0.250 and ≤0.125, respectively, in analogy to the common method of setting limits for analytical bias based on between-individual SD. Results: The values for the calculated SDRs depended upon the distribution patterns of test results: skewness toward higher values makes SDR LL lower and SDR UL higher. However, the CV of the regression line slope, CV( b ), is less affected by skewness. The average of SDR LL and SDR UL (aveSDR) correlates closely with CV ( b ) (r=0.995). The aveSDRs of ≤0.25 and ≤0.125 corresponds approximately to CV ( b ) values of ≤11% and ≤5.5%, respectively. For all results (i.e., n=80), conversion was allowable (optimal) in 98% (89%) of the analytes, as judged by CV ( b ). Resampling studies using random subsets of data with a data size (n) of 70 to 20 revealed that SDRs and CV ( b ) gradually increase with reduction of n, especially with n ≤30. Conclusions: CV ( b ) is a robust estimator for judging the convertibility of reference values among laboratories, even with a skewed distribution. Assuming 40 sera to be a practical size for the panel, reference values of 89% (80%) of analytes examined were made comparable by regression analysis with the allowable (optimal) level of precision.