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However, this comparison may be biased by regression to the mean.
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Additionally, it is possible that our stratified analyses are biased by regression to the mean.
When interpreting treatment results for persistent disease, one should keep in mind these findings, because results might be biased by the spontaneous regression of late-responding tumors.
Logistic regression can be biased by errors at extreme concentrations, and PCR data often shows concentrations spanning several orders of magnitude.
Prior ICU organizational studies used only historical controls (i.e. before-after studies) and can be biased by coincident interventions, temporal trends and regression towards the mean [ 7, 8].
54 Finally, the effect estimates in the regression models may be biased by confounding factors.
They propose that our studies may be biased by use of time-varying exposures in Cox regression models.
However, the results of these studies may be biased by a phenomenon known as 'regression to the mean' in that, because patients tend to be treated with a second agent at the height of their disease activity, there is a greater than 50-50 likelihood that disease activity will start improving after the intervention purely by chance [ 24].
For this reason, we do not believe that these results are biased by a regression to the mean effect.
Because we included all eligible patients in 1996 (rather than selecting patients based on specific HbA1c levels), our results are not biased by "regression to the mean" seen in other studies that pre-select patients at one of the extremes of the outcome distribution.
Hence, the estimation of heritability and additive variance with parent-offspring regression were not seriously biased by, e.g. shared environment between parents and offspring.
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