bias and unnecessary adjustment in epidemiologic studies.
However, mental attitude may alter the time course of disease processes and influence health behaviors directly, so the possibility of overadjustment
exists and we may be adjusting for the effect of intermediate factors in the causal pathway.
There are two types of risk: the infra-adjustment that indicates that the model does not have enough information to predict samples and the overadjustment
that indicates that the model has a lot of information that is not useful.
This allows young cohorts via an "overadjustment
" to the retirement age to hedge some of the longevity risk in the discounted cash flows associated with the payments of already retired cohorts.
Adding an increasing number of trees to the model does not result in overadjustment
. The main limitation of increasing ntree is the additional computation time.
First, there is overadjustment
when the data have not been prepared well, and there are data with erroneous or poorly conditioned input information.
On a public health level, systematic failure in appropriate medical coding may result in under- or overadjustment
to case-mix measurements when assessing quality of care .
As a comparison, the Whitehall study adjusted for 3 confounding factors  so overadjustment
cannot be ruled out in the current study.
To avoid overadjustment
, the only variables added to the model were those that were significant predictors of a secondary event at an a-level of 0.1 or that changed the parameter estimates for the main variables (galectin-3) by more than 10%.
Therefore, using this line item to offset related party holdings may generate an overadjustment
You can never prove cause and effect with observational studies, and it would be a mistake to make meaningful conclusions from this study due to its observational nature and possible overadjustment
of the data.
Finally, the statistical adjustment procedures applied to HIV surveillance data to account for reporting delay are subject to a degree of uncertainty (1), which could result in overadjustment
or underadjustment of the data.