![]() Our own experiences focus on randomized trials of cancer screening, where the mortality deficits produced by cancer screening are delayed. The researchers differ in their reasons for obtaining such data, and in the number of studies involved. Since it is not always possible to obtain the raw data directly from the authors, one is forced to make do with the information that can be recovered from the articles. Researchers often wish to carry out additional calculations or analyses using the survival data from studies of other authors. Compared with previous approaches, one advantage of ours is that there is no observer variation: there is no need to repeat the digitization process, since the extraction is completely replicable. When it is not possible to obtain the raw data from the authors, reconstruction techniques are a valuable alternative. We found that the PostScript used by Stata discloses considerably more of the data hidden behind survival curves than that generated by other statistical packages. If the original images can be obtained as a PostScript file, the data recovered from it can then be either input into these tools or processed directly. If the raster-based images are available, one can reliably recover much of the original information that seems to be ‘hidden’ beneath published survival curves. We focus on the additional precision, and elimination of observer variation, achieved by using vector-based formats rendered by PostScript, rather than the lower resolution image-based formats that have been analyzed up to now. Using examples, and a formal error analysis, we illustrate the extent to which, with what accuracy and precision, and in what circumstances, this information can be recovered from the various electronic formats in which such curves are published. Instead of using a digitizer to read in the coordinates from a raster image, we propose directly reading in the lines of the PostScript file of a vector image. Several authors have proposed methods/tools for extracting data from such curves using a digitizing software. When it is not possible to obtain the raw data directly, reconstruction techniques provide a valuable alternative. Researchers often wish to carry out additional calculations or analyses using the survival data from one or more studies of other authors. ![]()
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