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MUSINGS - REVELATIONS - REVIEWS

methodology

Statistical methods

Are doctors experts on life expectancy?

In Doctors are not experts on life expectancy1 David Strauss and Robert Shavelle noted that some clinicians testifying as expert witnesses on life expectancy did not have a very good grasp of the subject. As a result some were providing confusing and/or surprising opinions. The authors provided a number of examples. We can confirm that such misstatements continue to be made in this setting today, but the question of whether doctors are experts on life expectancy is not settled by such examples.

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Immortal time bias: A source of bias in estimating life expectancy and other measures

One of the most important aspects of good research is proper study design; no type or amount of statistical analysis can make up for a poorly designed study. In longitudinal research one of the most important aspects of study design is making sure that the temporal sequence of events is understood and recorded correctly. Errors in this arena can lead to misclassification of exposure time and differential follow-up between comparison groups. It is therefore crucial to understand time at risk in studies and correctly and fairly apply rules of follow-up to study subjects.

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Losing sleep over denominators, Part III: Explaining the error and the bias in Plioplys 1998

As we saw in Part II of this three part series, there is something wrong with Figure 4 in Plioplys et al. 1998.1 As a matter of fact, there is something wrong with all of the figures in the study, though it is a bit more difficult in some cases to confirm this. If the reader should like to work out the details for another, Figure 2 is a fairly easy place to start. In Figure 4, as we have seen, data that should apparently run out by age 11 years continues all the way to age 34 years. Did the authors create these curves out of whole cloth?

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