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Assessing assumptions for statistical analyses in randomised clinical trials

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Author

Nielsen, Emil Eik ; Nørskov, Anders Kehlet ; Lange, Theis ; Thabane, Lehana ; Wetterslev, Jørn ; Beyersmann, Jan ; de Uña-Álvarez, Jacobo ; Torri, Valter ; Billot, Laurent ; Putter, Hein ; Winkel, Per ; Gluud, Christian ; Jakobsen, Janus Christian. / Assessing assumptions for statistical analyses in randomised clinical trials. I: BMJ Evidence-Based Medicine. 2019.

Bibtex

@article{e22f2f883359455caae9cccb4c434867,
title = "Assessing assumptions for statistical analyses in randomised clinical trials",
abstract = "In order to ensure the validity of results of randomised clinical trials and under some circumstances to optimise statistical power, most statistical methods require validation of underlying statistical assumptions. The present paper describes how trialists in major medical journals report tests of underlying statistical assumptions when analysing results of randomised clinical trials. We also consider possible solutions how to improve current practice by adequate reporting of tests of underlying statistical assumptions. We conclude that there is a need to reach consensus on which underlying assumptions should be assessed, how these underlying assumptions should be assessed and what should be done if the underlying assumptions are violated.",
author = "Nielsen, {Emil Eik} and N{\o}rskov, {Anders Kehlet} and Theis Lange and Lehana Thabane and J{\o}rn Wetterslev and Jan Beyersmann and {de U{\~n}a-{\'A}lvarez}, Jacobo and Valter Torri and Laurent Billot and Hein Putter and Per Winkel and Christian Gluud and Jakobsen, {Janus Christian}",
note = "{\circledC} Author(s) (or their employer(s)) 2019. No commercial re-use. See rights and permissions. Published by BMJ.",
year = "2019",
month = "4",
day = "4",
doi = "10.1136/bmjebm-2019-111174",
language = "English",
journal = "Evidence-Based Medicine",
issn = "1356-5524",
publisher = "B M J Group",

}

RIS

TY - JOUR

T1 - Assessing assumptions for statistical analyses in randomised clinical trials

AU - Nielsen, Emil Eik

AU - Nørskov, Anders Kehlet

AU - Lange, Theis

AU - Thabane, Lehana

AU - Wetterslev, Jørn

AU - Beyersmann, Jan

AU - de Uña-Álvarez, Jacobo

AU - Torri, Valter

AU - Billot, Laurent

AU - Putter, Hein

AU - Winkel, Per

AU - Gluud, Christian

AU - Jakobsen, Janus Christian

N1 - © Author(s) (or their employer(s)) 2019. No commercial re-use. See rights and permissions. Published by BMJ.

PY - 2019/4/4

Y1 - 2019/4/4

N2 - In order to ensure the validity of results of randomised clinical trials and under some circumstances to optimise statistical power, most statistical methods require validation of underlying statistical assumptions. The present paper describes how trialists in major medical journals report tests of underlying statistical assumptions when analysing results of randomised clinical trials. We also consider possible solutions how to improve current practice by adequate reporting of tests of underlying statistical assumptions. We conclude that there is a need to reach consensus on which underlying assumptions should be assessed, how these underlying assumptions should be assessed and what should be done if the underlying assumptions are violated.

AB - In order to ensure the validity of results of randomised clinical trials and under some circumstances to optimise statistical power, most statistical methods require validation of underlying statistical assumptions. The present paper describes how trialists in major medical journals report tests of underlying statistical assumptions when analysing results of randomised clinical trials. We also consider possible solutions how to improve current practice by adequate reporting of tests of underlying statistical assumptions. We conclude that there is a need to reach consensus on which underlying assumptions should be assessed, how these underlying assumptions should be assessed and what should be done if the underlying assumptions are violated.

U2 - 10.1136/bmjebm-2019-111174

DO - 10.1136/bmjebm-2019-111174

M3 - Journal article

JO - Evidence-Based Medicine

JF - Evidence-Based Medicine

SN - 1356-5524

ER -

ID: 56951368