Using simulation studies to evaluate statistical methods

Simulation studies are computer experiments that involve creating data by pseudo‐random sampling. A key strength of simulation studies is the ability to understand the behavior of statistical methods because some “truth” (usually some parameter/s of interest) is known from the process of generating...

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Vydané v:Statistics in medicine Ročník 38; číslo 11; s. 2074 - 2102
Hlavní autori: Morris, Tim P., White, Ian R., Crowther, Michael J.
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: England Wiley Subscription Services, Inc 20.05.2019
John Wiley and Sons Inc
Predmet:
Bias
Biostatistics - methods
Computer Simulation
graphics for simulation
Guidelines as Topic
Models, Statistical
Monte Carlo
Monte Carlo Method
Research Design
Simulation
simulation design
simulation reporting
simulation studies
Statistical methods
Terminology
Tutorial in Biostatistics
simulation studies
graphics for simulation
Monte Carlo
simulation reporting
simulation design
ISSN:0277-6715, 1097-0258, 1097-0258
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Popis
Shrnutí:Simulation studies are computer experiments that involve creating data by pseudo‐random sampling. A key strength of simulation studies is the ability to understand the behavior of statistical methods because some “truth” (usually some parameter/s of interest) is known from the process of generating the data. This allows us to consider properties of methods, such as bias. While widely used, simulation studies are often poorly designed, analyzed, and reported. This tutorial outlines the rationale for using simulation studies and offers guidance for design, execution, analysis, reporting, and presentation. In particular, this tutorial provides a structured approach for planning and reporting simulation studies, which involves defining aims, data‐generating mechanisms, estimands, methods, and performance measures (“ADEMP”); coherent terminology for simulation studies; guidance on coding simulation studies; a critical discussion of key performance measures and their estimation; guidance on structuring tabular and graphical presentation of results; and new graphical presentations. With a view to describing recent practice, we review 100 articles taken from Volume 34 of Statistics in Medicine, which included at least one simulation study and identify areas for improvement.
Bibliografia:Tim P. Morris, 90 High Holborn, London WC1V 6LJ, United Kingdom.
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SourceType-Scholarly Journals-1
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ISSN:0277-6715
1097-0258
1097-0258
DOI:10.1002/sim.8086