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Results by year

Table representation of search results timeline featuring number of search results per year.

Year Number of Results
1953 1
1964 1
1965 1
1966 1
1968 1
1973 2
1974 2
1975 8
1976 3
1977 3
1978 1
1979 2
1980 2
1981 6
1982 4
1983 3
1984 6
1985 5
1986 4
1987 9
1988 12
1989 8
1990 15
1991 10
1992 17
1993 25
1994 21
1995 23
1996 23
1997 34
1998 23
1999 33
2000 40
2001 40
2002 45
2003 49
2004 57
2005 72
2006 79
2007 91
2008 116
2009 116
2010 120
2011 144
2012 142
2013 197
2014 214
2015 225
2016 256
2017 261
2018 294
2019 309
2020 313
2021 381
2022 399
2023 372
2024 458
2025 570
2026 453
2027 1

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Search Results

5,351 results

Results by year

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Page 1
Bias and causal associations in observational research.
Grimes DA, Schulz KF. Grimes DA, et al. Lancet. 2002 Jan 19;359(9302):248-52. doi: 10.1016/S0140-6736(02)07451-2. Lancet. 2002. PMID: 11812579
With respect to internal validity, selection bias, information bias, and confounding are present to some degree in all observational research. Selection bias stems from an absence of comparability between groups being studied. Information bias results from incorrect …
With respect to internal validity, selection bias, information bias, and confounding are present to some degree in all observational …
Automation bias and verification complexity: a systematic review.
Lyell D, Coiera E. Lyell D, et al. J Am Med Inform Assoc. 2017 Mar 1;24(2):423-431. doi: 10.1093/jamia/ocw105. J Am Med Inform Assoc. 2017. PMID: 27516495 Free PMC article.
Automation bias (AB) happens when users become overreliant on decision support, which reduces vigilance in information seeking and processing. Most research originates from the human factors literature, where the prevailing view is that AB occurs only in multitasking envir …
Automation bias (AB) happens when users become overreliant on decision support, which reduces vigilance in information seeking and pr …
Assessing bias in studies of prognostic factors.
Hayden JA, van der Windt DA, Cartwright JL, Côté P, Bombardier C. Hayden JA, et al. Ann Intern Med. 2013 Feb 19;158(4):280-6. doi: 10.7326/0003-4819-158-4-201302190-00009. Ann Intern Med. 2013. PMID: 23420236
This article describes the Quality In Prognosis Studies tool, which includes questions related to these areas that can inform judgments of risk of bias in prognostic research.A working group comprising epidemiologists, statisticians, and clinicians developed the tool as th …
This article describes the Quality In Prognosis Studies tool, which includes questions related to these areas that can inform judgmen …
A structural approach to selection bias.
Hernán MA, Hernández-Díaz S, Robins JM. Hernán MA, et al. Epidemiology. 2004 Sep;15(5):615-25. doi: 10.1097/01.ede.0000135174.63482.43. Epidemiology. 2004. PMID: 15308962
We describe examples of selection bias in case-control studies (eg, inappropriate selection of controls) and cohort studies (eg, informative censoring). We argue that the causal structure underlying the bias in each example is essentially the same: conditioning on a common …
We describe examples of selection bias in case-control studies (eg, inappropriate selection of controls) and cohort studies (eg, informat …
Information loss and bias in likert survey responses.
Westland JC. Westland JC. PLoS One. 2022 Jul 28;17(7):e0271949. doi: 10.1371/journal.pone.0271949. eCollection 2022. PLoS One. 2022. PMID: 35901102 Free PMC article.
These theoretical possibilities were tested using a large survey with 14 Likert-scaled questions presented to 125,387 respondents in 442 distinct behavioral-demographic groups. Despite the potential for bias and information loss, the empirical analysis found strong support …
These theoretical possibilities were tested using a large survey with 14 Likert-scaled questions presented to 125,387 respondents in 442 dis …
Expectation bias and information content.
Dauter Z, Weiss MS, Einspahr H, Baker EN. Dauter Z, et al. Acta Crystallogr D Biol Crystallogr. 2013 Feb;69(Pt 2):141. doi: 10.1107/S0907444913000255. Epub 2013 Jan 19. Acta Crystallogr D Biol Crystallogr. 2013. PMID: 23385450 No abstract available.
Bias in O-Information Estimation.
Gehlen J, Li J, Hourican C, Tassi S, Mishra PP, Lehtimäki T, Kähönen M, Raitakari O, Bosch JA, Quax R. Gehlen J, et al. Entropy (Basel). 2024 Sep 30;26(10):837. doi: 10.3390/e26100837. Entropy (Basel). 2024. PMID: 39451914 Free PMC article.
A popular method of attempting to estimate the higher-order relationships of synergy and redundancy from data is through the O-information. It is an information-theoretic measure composed of Shannon entropy terms that quantifies the balance between redundancy and sy …
A popular method of attempting to estimate the higher-order relationships of synergy and redundancy from data is through the O-informatio …
Expectation bias and information content.
Dauter Z, Weiss MS, Einspahr H, Baker EN. Dauter Z, et al. Acta Crystallogr Sect F Struct Biol Cryst Commun. 2013 Feb 1;69(Pt 2):83. doi: 10.1107/S1744309113001486. Epub 2013 Jan 19. Acta Crystallogr Sect F Struct Biol Cryst Commun. 2013. PMID: 23385742 Free PMC article.
Selection bias and information bias in clinical research.
Tripepi G, Jager KJ, Dekker FW, Zoccali C. Tripepi G, et al. Nephron Clin Pract. 2010;115(2):c94-9. doi: 10.1159/000312871. Epub 2010 Apr 21. Nephron Clin Pract. 2010. PMID: 20407272 Review.
On the other hand, systematic error or bias reflects a problem of validity of the study and arises because of any error resulting from methods used by the investigator when recruiting individuals for the study, from factors affecting the study participation (selection bias) or fr …
On the other hand, systematic error or bias reflects a problem of validity of the study and arises because of any error resulting from metho …
[Definition, concept, and practical example of information bias].
Suzuki S. Suzuki S. Nihon Koshu Eisei Zasshi. 2026 Jul 1;73(6):567-573. doi: 10.11236/jph.25-088. Epub 2026 Mar 3. Nihon Koshu Eisei Zasshi. 2026. PMID: 41780971 Free article. Japanese.
Using a real-world example, the paper examines the underlying mechanism and emphasizes the importance of precise covariate definition in study design.Methods Information bias is defined as "a flaw in measuring exposure, covariate, or outcome variables that results in diffe …
Using a real-world example, the paper examines the underlying mechanism and emphasizes the importance of precise covariate definition in stu …
5,351 results