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Data and Analyses

In order to promote transparency and clarity of the analyses performed in support of EPA's Supplemental Guidance for Assessing Susceptibility from Early-Life Exposure to Carcinogens, the data and the analyses are now available on this web site. The data is presented in two different formats:

The data input into the analyses are presented first in four Excel spreadsheets. These spreadsheets are identified below, along with a short description of the data each contains.

A separate Excel spreadsheet presents EPA's calculations of the inverse variance weighted geometric means.

To perform the calculations, EPA used the statistical programming language and environment R. This is a freely available Open Source implementation of the S programming language, described in "R: A Language and Environment for Statistical Computing" by the R Development Core Team (ISBN 3-900051-07-0). It is available, along with extensive documentation, at http://www.R-project.org Exit EPA Disclaimer. At that web site are full instructions for downloading and installing R on Windows, Linux/Unix, and Mac OS X. The files included here should run on any of those operating systems.

The attached zip file contains the Excel data files described above (lifetime.csv, mutacute.csv, mutrep.csv, nmrep.csv, and elife calc.xls) along with two "Read Me" files and the programming files. The two directories in this folder contain the data files and scripts that were used to calculate the posterior distributions for juvenile to adult potency ratios in the Supplemental Guidance as well as the Environmental Health Perspectives paper, "Assessing Susceptibility from Early-Life Exposure to Carcinogens," Barton et al., 2005. The directory "Revised2Data" contains four comma-delimited value files with the data for all the studies reviewed in this paper. They are divided into files by experimental design and, largely, by mode of action (mutagen versus non-mutagen).

These analyses were carried out exclusively using the statistical programming language and environment R. This is a freely available Open Source implementation of the S programming language, described in "R: A Language and Environment for Statistical Computing" by the R Development Core Team (ISBN 3-900051-07-0). It is available, along with extensive documentation, at http://www.R-project.org Exit EPA Disclaimer. At that web site are full instructions for downloading and installing R on Windows, Linux/Unix, and Mac OS X. The files included here should run on any of the operating systems listed.

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