Accounting for Expected Adjusted Effect

The point that adjustment for confounders do not always guarantee protection against spurious findings and type 1-errors has been made before. The present simulation study indicates that for traditional regression methods, this risk is accentuated by a large sample size, low reliability in the measu...

Descripción completa

Detalles Bibliográficos
Autores principales: Sorjonen, Kimmo, Melin, Bo, Ingre, Michael
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Psychology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7528751/
https://www.ncbi.nlm.nih.gov/pubmed/33041911
http://dx.doi.org/10.3389/fpsyg.2020.542082
_version_ 1783589322450010112
author Sorjonen, Kimmo
Melin, Bo
Ingre, Michael
author_facet Sorjonen, Kimmo
Melin, Bo
Ingre, Michael
author_sort Sorjonen, Kimmo
collection PubMed
description The point that adjustment for confounders do not always guarantee protection against spurious findings and type 1-errors has been made before. The present simulation study indicates that for traditional regression methods, this risk is accentuated by a large sample size, low reliability in the measurement of the confounder, and high reliability in the measurement of the predictor and the outcome. However, this risk might be attenuated by calculating the expected adjusted effect, or the required reliability in the measurement of the possible confounder, with equations presented in the present paper.
format Online
Article
Text
id pubmed-7528751
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher Frontiers Media S.A.
record_format MEDLINE/PubMed
spelling pubmed-75287512020-10-09 Accounting for Expected Adjusted Effect Sorjonen, Kimmo Melin, Bo Ingre, Michael Front Psychol Psychology The point that adjustment for confounders do not always guarantee protection against spurious findings and type 1-errors has been made before. The present simulation study indicates that for traditional regression methods, this risk is accentuated by a large sample size, low reliability in the measurement of the confounder, and high reliability in the measurement of the predictor and the outcome. However, this risk might be attenuated by calculating the expected adjusted effect, or the required reliability in the measurement of the possible confounder, with equations presented in the present paper. Frontiers Media S.A. 2020-09-17 /pmc/articles/PMC7528751/ /pubmed/33041911 http://dx.doi.org/10.3389/fpsyg.2020.542082 Text en Copyright © 2020 Sorjonen, Melin and Ingre. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Psychology
Sorjonen, Kimmo
Melin, Bo
Ingre, Michael
Accounting for Expected Adjusted Effect
title Accounting for Expected Adjusted Effect
title_full Accounting for Expected Adjusted Effect
title_fullStr Accounting for Expected Adjusted Effect
title_full_unstemmed Accounting for Expected Adjusted Effect
title_short Accounting for Expected Adjusted Effect
title_sort accounting for expected adjusted effect
topic Psychology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7528751/
https://www.ncbi.nlm.nih.gov/pubmed/33041911
http://dx.doi.org/10.3389/fpsyg.2020.542082
work_keys_str_mv AT sorjonenkimmo accountingforexpectedadjustedeffect
AT melinbo accountingforexpectedadjustedeffect
AT ingremichael accountingforexpectedadjustedeffect

Ejemplares similares