File:Length time bias.svg

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Original file(SVG file, nominally 341 × 384 pixels, file size: 31 KB)

Summary

Illustration of one possible manifestation of length time bias. The illustration represents the life spans of several patients who are known to have developed cancer during a certain time frame. At one point in time, all of the still-living patients were tested for cancer using a 100 % accurate screening test. The patients whose cancers were discovered by the screen are highlighted in blue, the ones who either died before they could be screened or did not develop the cancer until after the screening are shown in black. Since the patients who ultimately survive their cancers have it for a longer period of time (possibly because they have a less aggressive form), they are more likely to be caught by the screen than patients who quickly develop and then die from more aggressive cancers. This biases the numbers so that it appears that patients who are detected through screening have a better chance of surviving, even if none of the patients are ever treated.

Licensing

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File history

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Date/TimeThumbnailDimensionsUserComment
current15:22, 17 January 2017Thumbnail for version as of 15:22, 17 January 2017341 × 384 (31 KB)127.0.0.1 (talk)Illustration of one possible manifestation of length time bias. The illustration represents the life spans of several patients who are known to have developed cancer during a certain time frame. At one point in time, all of the still-living patients were tested for cancer using a 100 % accurate screening test. The patients whose cancers were discovered by the screen are highlighted in blue, the ones who either died before they could be screened or did not develop the cancer until after the screening are shown in black. Since the patients who ultimately survive their cancers have it for a longer period of time (possibly because they have a less aggressive form), they are more likely to be caught by the screen than patients who quickly develop and then die from more aggressive cancers. This biases the numbers so that it appears that patients who are detected through screening have a better chance of surviving, even if none of the patients are ever treated.
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