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Clinical Chemistry 18: 244-249, 1972;
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Clinical Chemistry, Vol 18, 244-249, Copyright © 1972 by the American Association for Clinical Chemistry

Effects of Intra- and Inter-Individual Variation on Distributions of Single Measurements

Eugene K. Harris 1 and David L. DeMets 1

1 Laboratory of Applied Studies, Division of Computer Research and Technology, NIH, USPHS, Bethesda, Md. 20014.

When healthy individuals are surveyed to estimate the "normal range" of some measured variable, generally only a single determination of the variable is obtained for each person. The distribution of such values reflects intra-individual variations, (including analytic deviations) as well as the differences among individuals with respect to such parameters as mean or variance. These underlying sources of variation have been expressed in a conditional probability model from which general equations have been derived showing the effects of these variations on the shape parameters (skewness and kurtosis) of a single-sample distribution. These results may help to explain the shape of a given distribution. More generally, they imply that methods of calculating normal ranges would benefit from a study of various mathematical transformations that could convert distributions of almost any shape to approximately gaussian form. Data from recent blood-chemistry studies are used to compare observed shape statistics with those calculated from the model.


Key Words: conditional probability functions • inter- and intra-individual variation • establishing the normal range of values • gaussian and nongaussian distributions • assumptionless equations for distribution

Submitted on June 4, 1971
Accepted on November 26, 1971






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Copyright © 1972 by the American Association for Clinical Chemistry.