Examining life table results to detect assumption violations

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Potential assumption violations may be masked by the grouped nature of the data. If the individual (ungrouped) data measurements are available, they can be examined for signs of lack of independence or lack of uniformity in the censoring. However, when examining life table results, you should keep these potential problems in mind, along with the possibility of implicit factors not surfaced in the data.

The problems detectable from the life table results themselves are generally related to problems due to lack of data.

Examining results for a life table analysis:

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