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A geometric mean provides a better estimate of central tendency for data that are distributed with a long tail at the upper end of the distribution. This
type of distribution is common in the measurement of  environmental chemicals in blood or urine. The geometric mean is influenced less by high values than is the arithmetic mean. Geometric means were calculated by taking the log of each concentration and then computing the weighted mean
of those log-transformed values using SUDAAN software. Ninety-five  percent  confidence  intervals  around  this weighted mean were calculated by adding and subtracting an amount equal to the product of a Student¡¯s t-statistic and the standard error of the weighted mean estimate. The degrees
of freedom of the t-statistic were determined by subtracting the number of strata from the number of primary sampling units  (PSUs)  according  to  the  data  available  from  the complex survey design. The standard error was computed with SUDAAN¡¯s Proc Descript (design=WR), which uses
Taylor series linearization for variance estimation. The weighted geometric mean and its confidence limits were then obtained by taking the antilogs of this weighted mean and its upper and lower confidence limits.

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