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Where to look for the most frequent biases?

Study quality depends on a number of factors, one of them being internal validity. Such validity can be affected by random and systematic error, the latter also known as bias. Both make it more difficult to assess a correct frequency or the true relationship between exposure and outcome. Where rando...

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Detalles Bibliográficos
Autores principales: Jager, Kitty J., Tripepi, Giovanni, Chesnaye, Nicholas C., Dekker, Friedo W., Zoccali, Carmine, Stel, Vianda S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley & Sons Australia, Ltd 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7318122/
https://www.ncbi.nlm.nih.gov/pubmed/32133725
http://dx.doi.org/10.1111/nep.13706
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author Jager, Kitty J.
Tripepi, Giovanni
Chesnaye, Nicholas C.
Dekker, Friedo W.
Zoccali, Carmine
Stel, Vianda S.
author_facet Jager, Kitty J.
Tripepi, Giovanni
Chesnaye, Nicholas C.
Dekker, Friedo W.
Zoccali, Carmine
Stel, Vianda S.
author_sort Jager, Kitty J.
collection PubMed
description Study quality depends on a number of factors, one of them being internal validity. Such validity can be affected by random and systematic error, the latter also known as bias. Both make it more difficult to assess a correct frequency or the true relationship between exposure and outcome. Where random error can be addressed by increasing the sample size, a systematic error in the design, the conduct or the reporting of a study is more problematic. In this article, we will focus on bias, discuss different types of selection bias (sampling bias, confounding by indication, incidence‐prevalence bias, attrition bias, collider stratification bias and publication bias) and information bias (recall bias, interviewer bias, observer bias and lead‐time bias), indicate the type of studies where they most frequently occur and provide suggestions for their prevention.
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spelling pubmed-73181222020-06-29 Where to look for the most frequent biases? Jager, Kitty J. Tripepi, Giovanni Chesnaye, Nicholas C. Dekker, Friedo W. Zoccali, Carmine Stel, Vianda S. Nephrology (Carlton) Review Article Study quality depends on a number of factors, one of them being internal validity. Such validity can be affected by random and systematic error, the latter also known as bias. Both make it more difficult to assess a correct frequency or the true relationship between exposure and outcome. Where random error can be addressed by increasing the sample size, a systematic error in the design, the conduct or the reporting of a study is more problematic. In this article, we will focus on bias, discuss different types of selection bias (sampling bias, confounding by indication, incidence‐prevalence bias, attrition bias, collider stratification bias and publication bias) and information bias (recall bias, interviewer bias, observer bias and lead‐time bias), indicate the type of studies where they most frequently occur and provide suggestions for their prevention. John Wiley & Sons Australia, Ltd 2020-03-27 2020-06 /pmc/articles/PMC7318122/ /pubmed/32133725 http://dx.doi.org/10.1111/nep.13706 Text en © 2020 The Authors. Nephrology published by John Wiley & Sons Australia, Ltd on behalf of Asian Pacific Society of Nephrology. This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.
spellingShingle Review Article
Jager, Kitty J.
Tripepi, Giovanni
Chesnaye, Nicholas C.
Dekker, Friedo W.
Zoccali, Carmine
Stel, Vianda S.
Where to look for the most frequent biases?
title Where to look for the most frequent biases?
title_full Where to look for the most frequent biases?
title_fullStr Where to look for the most frequent biases?
title_full_unstemmed Where to look for the most frequent biases?
title_short Where to look for the most frequent biases?
title_sort where to look for the most frequent biases?
topic Review Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7318122/
https://www.ncbi.nlm.nih.gov/pubmed/32133725
http://dx.doi.org/10.1111/nep.13706
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