survival bias

A bias that occurs when cancer survival confounds analysis of exposure

survival bias

The tendency of people who live longer after an illness or injury to receive more medical care. The medical care may not be the cause of the patients' longevity; rather, the care may be an effect of it.
References in periodicals archive ?
Moreover, specifically asking for exposure in a particular time frame may have been limited by recall bias and including patients in a relatively good clinical condition could have led to survival bias.
For example, the impact of one of the clinical factors, age, may even introduce a survival bias on genotype frequencies that is difficult to model, and the authors' analysis does not explicitly address the possibility that the clinical characteristics alone might be more precise indicators of prescription threshold than genotype information alone.
These differences over time probably are a result of survival bias, the investigators suggested.
Caplan is probably correct in noting that the Columbia University study on the effect of TC and LDL-C on mortality was subject to survival bias, indication bias, and possibly better medical care in general for the statin users.
The literature on survival bias for stocks is discussed in the second section.
They reinforce the conclusion from previous studies that, even adjusting for survival bias, mutual fund performance is truly persistent.
Since student withdrawal data was omitted, the results of the study are subjected to survival bias.
In the absence of commonality, a sample average can possess substantial survival bias but can still equal the appropriate inference about an asset's expected return.
One procedure to ameliorate the impact of survival bias without encountering the above problem is to match the sample firms with control firms on the basis of survival.
If so, does the statistical survival bias for ochre favour sandstone shelters as art sites, or do sandstone shelters favour ochre dominance in the surviving sample?
To evaluate the survival bias in analyzing the relationship between the Glu298Asp mutation and progression to chronic renal failure, we divided the patients into two groups according to the duration of hemodialysis; among the diabetics, patients who had experienced >5 years of hemodialysis were placed in the long-term survival group, whereas patients with hemodialysis <5 years were placed in the short-term group.
Through simulation and analysis of emerging market histories, we show that statistics about emerging markets may be strongly biased by survival bias and by "sorting" bias.