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Avoiding bias in se...
Avoiding bias in self-controlled case series studies of coronavirus disease 2019
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- Fonseca-Rodríguez, Osvaldo (författare)
- Umeå universitet,Institutionen för klinisk mikrobiologi
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- Connolly-Andersen, Anne-Marie (författare)
- Umeå universitet,Institutionen för klinisk mikrobiologi
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- Katsoularis, Ioannis (författare)
- Umeå universitet,Avdelningen för medicin
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- Lindmark, Krister (författare)
- Umeå universitet,Avdelningen för medicin
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- Farrington, Paddy (författare)
- School of Mathematics and Statistics, The Open University, Milton Keynes, United Kingdom
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(creator_code:org_t)
- 2021-09
- 2021
- Engelska.
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Ingår i: Statistics in Medicine. - : John Wiley & Sons. - 0277-6715 .- 1097-0258. ; 40:27, s. 6197-6208
- Relaterad länk:
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https://onlinelibrar...
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https://urn.kb.se/re...
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https://doi.org/10.1...
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Abstract
Ämnesord
Stäng
- Many studies, including self-controlled case series (SCCS) studies, are being undertaken to quantify the risks of complications following infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus that causes coronavirus disease 2019 (COVID-19). One such SCCS study, based on all COVID-19 cases arising in Sweden over an 8-month period, has shown that SARS-CoV-2 infection increases the risks of AMI and ischemic stroke. Some features of SARS-CoV-2 infection and COVID-19, present in this study and likely in others, complicate the analysis and may introduce bias. In the present paper we describe these features, and explore the biases they may generate. Motivated by data-based simulations, we propose methods to reduce or remove these biases.
Ämnesord
- MEDICIN OCH HÄLSOVETENSKAP -- Klinisk medicin -- Infektionsmedicin (hsv//swe)
- MEDICAL AND HEALTH SCIENCES -- Clinical Medicine -- Infectious Medicine (hsv//eng)
Nyckelord
- bias
- cardiovascular disease
- COVID-19
- epidemiological methods
- mortality
- self-controlled case series
Publikations- och innehållstyp
- ref (ämneskategori)
- art (ämneskategori)
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