Setting a reference interval by means of exploratory data analysis

A reference interval in the inspection of a clinical chemical is important as a reference scale of inspection value. Outliers are often in the data sampled from the reference sample group to set this interval. It is contradictory that outliers must be removed to know the distribution, though the distribution must be known to remove outliers. Therefore it will be effective in setting the reference interval if a method is found to remove outliers and to estimate the percent points without assuming the distribution of data. The exploratory data analysis (EDA) proposed by Tukey et al. (1977) has these characteristics. In this paper, a method of setting the reference interval by means of the EDA is proposed and compared with the Maximum Likelihood Transformation Method (MLTM) by simulation. It is found that the precision of MLTM is affected by the outliers; however, they hardly affect the precision of the proposed method. It is concluded that the proposed method is robust toward the types of distribution and the outliers; thus it is effective for setting a reference interval.