A robust approach to reference interval estimation and evaluation

Abstract

We propose a new methodology for the estimation of reference intervals for data sets with small numbers of observations or for those with substantial numbers of outliers. We propose a prediction interval that uses robust estimates of location and scale. The SAS software can be readily modified to do these calculations. We compared four reference interval procedures (nonparametric, transformed, robust with a nonparametric lower limit, and transformed robust) for sample sizes of 20, 40, 60, 80, 100, and 120 from χ2 distributions of 1, 4, 7, and 10 df. χ2 distributions were chosen because they simulate the skewness of distributions often found in clinical chemistry populations. We used the root mean square error as the measure of performance and used computer simulation to calculate this measure. The robust estimator showed the best performance for small sample sizes. As the sample size increased, the performance values converged. The robust method for calculating upper reference interval values yields reasonable results. In two examples using real data for haptoglobin and glucose, the robust estimator provides slightly smaller upper reference limits than the other procedures. Lastly, the robust estimator was compared with the other procedures in a population where 5% of the values were multiplied by a factor of 5. The reference intervals were calculated with and without outlier detection. In this case, the robust approach consistently yielded upper reference interval values that were closer to those of the true underlying distributions. We propose that robust statistical analysis can be of great use for determinations of reference intervals from limited or possibly unreliable data.

Reference values for reticulocyte parameters and hypochromic RBC in healthy children

“…This article describes the determination of pediatric references values for reticulocyte parameters and hypochromic red blood cells assayed on ADVIA 2120 hematology analyzer. Age-and gender-specific reference intervals were constructed by the robust method [10] for four hematological parameters, sampled from 311 pediatric participants aged from 6 months to 18 years old. In this study, it was necessary to develop distinct reference values for male and female participants with 12-17 years of age, as Delta-He, IRF and %Hypo showed statistically significant gender differences in this group.…”

Circannual variation in plasma adrenocorticotropic hormone concentrations in the UK in normal horses and ponies, and those with pituitarypars intermediadysfunction

“…The Mann-Whitney test was then used to compare data from the 2 resulting distinct time periods. Upper 97.5% limits of reference intervals were calculated from a normal approximation of data and also by Horn's robust method (Horn et al 1998). Statistical analysis was performed using MedCalc 11.5.0.0 software 2 .…”

Sensitivity and specificity of normality tests and consequences on reference interval accuracy at small sample size: a computer‐simulation study

“…5 If data Gaussianity cannot be achieved despite transformation attempts, alternative methods, such as a nonparametric approach, which does not assume the distribution of analyte level in the reference population 6,7 , or the robust method, which is based on iterative processes that estimate the median and spread of the distribution, may be used. 6,8 Guidelines, which clearly indicate which statistical technique should be used based on the size of the sample, have been developed by the American Society of Veterinary Clinical Pathologists (ASVCP). 6 When at least 120 reference subjects are included in the sample, the nonparametric method should be used.…”