Let's practice what we preach: Planning and interpreting simulation studies with design and analysis of experiments

11/26/2021
by   Hugh Chipman, et al.
0

Statisticians recommend the Design and Analysis of Experiments (DAE) for evidence-based research but often use tables to present their own simulation studies. Could DAE do better? We outline how DAE methods can be used to plan and analyze simulation studies. Tools for planning include fishbone diagrams, factorial and fractional factorial designs. Analysis is carried out via ANOVA, main-effect and interaction plots and other DAE tools. We also demonstrate how Taguchi Robust Parameter Design can be used to study the robustness of methods to a variety of uncontrollable population parameters.

READ FULL TEXT
POST COMMENT

Comments

There are no comments yet.

Authors

page 1

page 2

page 3

page 4

12/08/2017

Using simulation studies to evaluate statistical methods

Simulation studies are computer experiments which involve creating data ...
09/09/2019

INTEREST: INteractive Tool for Exploring REsults from Simulation sTudies

Simulation studies allow us to explore the properties of statistical met...
09/14/2021

Automatic Reuse, Adaption, and Execution of Simulation Experiments via Provenance Patterns

Simulation experiments are typically conducted repeatedly during the mod...
11/01/2021

Computing with R-INLA: Accuracy and reproducibility with implications for the analysis of COVID-19 data

The statistical methods used to analyze medical data are becoming increa...
03/09/2022

A-Optimal Split Questionnaire Designs for Multivariate Continuous Variables

A split questionnaire design (SQD), an alternative to full questionnaire...
10/15/2020

An Artifact-based Workflow for Finite-Element Simulation Studies

Workflow support typically focuses on single simulation experiments. Thi...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.