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National Cancer Institute U.S. National Institutes of Health www.cancer.gov
Radiation Epidemiology Branch

Tools & Resources

  • Interactive Radioepidemiological Computer Program

  • Estimating Exposure to Iodine - 131

    During the Cold War in the 1950s and early 1960s, the U.S. Government conducted about one hundred nuclear weapons tests in the atmosphere at a test site in Nevada. As a result, people living in the U.S. at the time of the tests were exposed to varying levels of radiation, notably from Iodine-131 (I-131). The I-131 dose/risk calculator (entitled "Radioactive I-131 from Fallout") is a tool that allows any individual to obtain an estimate of the radiation exposure from I-131 that he or she received from the Nevada nuclear weapons tests and of the risk that he or she will develop a thyroid cancer resulting from that exposure.

  • Multiple Primary Cancer Risk Module (SEER*Stat)

  • Uncertainties in Radiation Dosimetry

  • Confidence Interval

    Simple, non-linear data transformations are often used so that data can be analyzed using normal-theory statistical methods. Results of such analyses, stated in terms of the mean or the variance of the transformed random variable, are not always appropriate; for example, it may be preferable to express the cancer risk of a population exposed to a pollutant as a multiple of the estimated mean exposure level, rather than as the same multiple of the median exposure level.

The median is obtained by applying the inverse transformation to the estimated mean of the transformed data.

Example:

If the natural logarithm of the measured pollution level is normally distributed with mean µ and variance σ2, the mean of the original variable is exp{µ + ½ σ2} whereas its median is exp{? }. For µ = 3 and σ2 = 1, the mean is exp{3.5} = 33.1 and the median is exp(3.0) = 20.1.

An exact algorithm for confidence interval estimation of the lognormal mean and, more generally, for linear functions of the normal mean and variance, has been known for some time but its application has involved some rather tedious calculations based on tabulated data.

The computer algorithm developed by Brad Lyon of Oak Ridge National Laboratory and Charles Land of the Radiation Epidemiology Branch, NCI, is very fast and has been extensively tested for accuracy.