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Immortal-time bias: a crucial yet overlooked confounder in urological research.

08:00 EDT 1st October 2017 | BioPortfolio

Summary of "Immortal-time bias: a crucial yet overlooked confounder in urological research."

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This article was published in the following journal.

Name: BJU international
ISSN: 1464-410X
Pages: 455

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Medical and Biotech [MESH] Definitions

The influence of study results on the chances of publication and the tendency of investigators, reviewers, and editors to submit or accept manuscripts for publication based on the direction or strength of the study findings. Publication bias has an impact on the interpretation of clinical trials and meta-analyses. Bias can be minimized by insistence by editors on high-quality research, thorough literature reviews, acknowledgement of conflicts of interest, modification of peer review practices, etc.

Any deviation of results or inferences from the truth, or processes leading to such deviation. Bias can result from several sources: one-sided or systematic variations in measurement from the true value (systematic error); flaws in study design; deviation of inferences, interpretations, or analyses based on flawed data or data collection; etc. There is no sense of prejudice or subjectivity implied in the assessment of bias under these conditions.

Any deviation of results or inferences from the truth, or processes leading to such deviation. Bias can result from several sources: one-sided or systematic variations in measurement from the true value (systematic error); flaws in study design; deviation of inferences, interpretations, or analyses based on flawed data or data collection; etc. There is no sense of prejudice or subjectivity implied in the assessment of bias under these conditions.

Adverse of favorable selection bias exhibited by insurers or enrollees resulting in disproportionate enrollment of certain groups of people.

The introduction of error due to systematic differences in the characteristics between those selected and those not selected for a given study. In sampling bias, error is the result of failure to ensure that all members of the reference population have a known chance of selection in the sample.

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