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Das ABC der medizinischen Statistik: Klinische Studien lesen und verstehen

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Das ABC der medizinischen Statistik : Klinische Studien lesen und verstehen. / Labenz, J.; Kunz, Cornelia U.

In: Der Internist, Vol. 51, No. 4, 04.2010, p. 489-99; quiz 500.

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Labenz, J. ; Kunz, Cornelia U. / Das ABC der medizinischen Statistik : Klinische Studien lesen und verstehen. In: Der Internist. 2010 ; Vol. 51, No. 4. pp. 489-99; quiz 500.

Bibtex

@article{7b57c1a3cc3744a190c6b5e0ca8f9aa3,
title = "Das ABC der medizinischen Statistik: Klinische Studien lesen und verstehen",
abstract = "Clinical trials test hypotheses that are accepted or rejected according to a predetermined probability of error (level of significance). Significance does not however mean relevance. Good parameters of relevance are absolute risk reduction and based on this the calculation of the number of patients who need to be treated for one additional patient to benefit. The randomized controlled trial is the gold standard for comparative evaluation of effects. In the ideal scenario it is designed so that a difference established by statistical methods becomes probable. In non-inferiority studies care should be taken that no equivalence is shown but rather that the difference is not greater than a predefined margin of error for differences. Meta-analyses of studies with similar endpoints have the potential to improve the level of evidence. Since the findings of meta-analyses depend on the studies included, critical assessment of the results is essential.",
keywords = "Clinical Trials as Topic, Computer Simulation, Data Interpretation, Statistical, Meta-Analysis as Topic, Models, Statistical",
author = "J. Labenz and Kunz, {Cornelia U.}",
year = "2010",
month = apr,
doi = "10.1007/s00108-010-2581-x",
language = "German",
volume = "51",
pages = "489--99; quiz 500",
journal = "Der Internist",
issn = "0020-9554",
publisher = "Springer Verlag",
number = "4",

}

RIS

TY - JOUR

T1 - Das ABC der medizinischen Statistik

T2 - Klinische Studien lesen und verstehen

AU - Labenz, J.

AU - Kunz, Cornelia U.

PY - 2010/4

Y1 - 2010/4

N2 - Clinical trials test hypotheses that are accepted or rejected according to a predetermined probability of error (level of significance). Significance does not however mean relevance. Good parameters of relevance are absolute risk reduction and based on this the calculation of the number of patients who need to be treated for one additional patient to benefit. The randomized controlled trial is the gold standard for comparative evaluation of effects. In the ideal scenario it is designed so that a difference established by statistical methods becomes probable. In non-inferiority studies care should be taken that no equivalence is shown but rather that the difference is not greater than a predefined margin of error for differences. Meta-analyses of studies with similar endpoints have the potential to improve the level of evidence. Since the findings of meta-analyses depend on the studies included, critical assessment of the results is essential.

AB - Clinical trials test hypotheses that are accepted or rejected according to a predetermined probability of error (level of significance). Significance does not however mean relevance. Good parameters of relevance are absolute risk reduction and based on this the calculation of the number of patients who need to be treated for one additional patient to benefit. The randomized controlled trial is the gold standard for comparative evaluation of effects. In the ideal scenario it is designed so that a difference established by statistical methods becomes probable. In non-inferiority studies care should be taken that no equivalence is shown but rather that the difference is not greater than a predefined margin of error for differences. Meta-analyses of studies with similar endpoints have the potential to improve the level of evidence. Since the findings of meta-analyses depend on the studies included, critical assessment of the results is essential.

KW - Clinical Trials as Topic

KW - Computer Simulation

KW - Data Interpretation, Statistical

KW - Meta-Analysis as Topic

KW - Models, Statistical

U2 - 10.1007/s00108-010-2581-x

DO - 10.1007/s00108-010-2581-x

M3 - Journal article

C2 - 20221576

VL - 51

SP - 489-99; quiz 500

JO - Der Internist

JF - Der Internist

SN - 0020-9554

IS - 4

ER -