Partitioning reference values of several Gaussian subpopulations with unequal prevalence--a procedure with computer program support.
BACKGROUND
To be able to interpret laboratory values, it is essential to develop population-based reference intervals. A crucial consideration is whether a reference interval should be divided into subpopulations or not, so-called partitioning. There are established methods for deciding whether partitioning should be done or not. However, these methods are only applicable when partitioning into two subpopulations is considered. The primary aim of this study was to suggest a procedure that was also valid for several subpopulations. The method assumes that these subpopulations are Gaussian. Furthermore, a secondary aim was to provide a tailor-made computer program to support calculations.


METHODS
The fundamental idea is to partition reference intervals if the proportions of the distributions of the subpopulations outside the combined reference limit deviate from the nominal value of 0.025. This is made possible by finding the combined reference interval using an equation solver algorithm.


RESULTS
It was found that an equation solver algorithm could easily identify the combined reference interval when combining two or more subpopulations, even if these subpopulations had unequal prevalences. It was also found that this could be done even if the ratio between samples does not reflect the ratio between prevalences. Using this algorithm, it was possible to study whether the proportion outside the combined reference limits in any of several subpopulations deviated from the nominal 0.025 by such a magnitude that partitioning was recommended. When similar figures to those found in earlier studies with other methods were tested, the procedure showed consistent results with these methods. The procedure was also found to be applicable when several subpopulations were considered. As a practical result of the study, a tailor-made computer program was developed and is now provided over the Internet.


CONCLUSIONS
The suggested procedure could serve as an alternative or complement to existing methods. The procedure provides calculations of the combined reference interval, even if sample fractions do not reflect prevalence fractions. The important advantage with the suggested procedure is the generalisation to the situation when several Gaussian subpopulations, possibly with unequal prevalences, are considered. Finally, since a tailor-made computer program is provided, the procedure is simple to use.
Gellerstedt
Martin
M
Department of Informatics, University West Sweden, Trollhättan, Sweden. martin.gellerstedt@hv.se
D000465:Algorithms; D019411:Clinical Laboratory Techniques / Q000706:statistics & numerical data*; D015233:Models, Statistical; D016011:Normal Distribution; D015995:Prevalence; D012016:Reference Values; D012984:Software