Accuracy in Parameter Estimation and Simulation Approaches for Sample Size Planning with Multiple Stimuli
Abstract
The planning of sample size for research studies often focuses on obtaining a significant result given a specified level of power, significance, and an anticipated effect size. This planning requires prior knowledge of the study design and a statistical analysis to calculate the proposed sample size. However, there may not be one specific testable analysis from which to derive power [@silberzahn2018many] or a hypothesis to test for the project (e.g., creation of a stimuli database). Modern power and sample size planning suggestions include accuracy in parameter estimation [AIPE, @kelley2007; @maxwell2008] and simulation of proposed analyses [@chalmers2020]. These toolkits provide flexibility in traditional power analyses that focus on the if-this, then-that approach, yet, both AIPE and simulation require either a specific parameter (e.g., mean, effect size, etc.) or statistical test for planning sample size. In this tutorial, we explore how AIPE and simulation approaches can be combined to accommodate studies that may not have a specific hypothesis test or wish to account for the potential of a multiverse of analyses. Specifically, we focus on studies that use multiple items and suggest that sample sizes can be planned to measure those items adequately and precisely, regardless of statistical test. This tutorial also provides multiple code vignettes and package functionality that researchers can adapt and apply to their own measures.
Authors 23
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Erin Michelle Buchanan corresponding
Harrisburg University of Science and Technology
Affiliation as printed
Analytics Harrisburg University of Science and Technology
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Mahmoud Medhat Elsherif Aachen
Leiden University · University of Leicester
Affiliation as printed
Department of Vision Sciences University of Leicester
Leiden University
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Affiliation as printed
Department of Psychology Princeton University
Marshall College
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Harrisburg University of Science and Technology
Affiliation as printed
Analytics Harrisburg University of Science and Technology
Illumin Analytics
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Stevens Institute of Technology
Affiliation as printed
Stevens Institute of Technology
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Affiliation as printed
Department of Neuroscience University of Padova
Padova Neuroscience Center
University of Padova
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Tom Heyman Aachen
Affiliation as printed
Methodology and Statistics Unit Institute of Psychology
Methodology and Statistics Unit Institute of Psychology Leiden University
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Affiliation as printed
Department of Developmental and Social Psychology University of Padova
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Affiliation as printed
KU Leuven
University of Leuven
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Affiliation as printed
Applied Memory Research Laboratory Institute of Psychology Jagiellonian University 11 Franklin and
Applied Memory Research Laboratory Institute of Psychology Jagiellonian University
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Harrisburg University of Science and Technology · Franklin & Marshall College
Affiliation as printed
Analytics Harrisburg University of Science and Technology
Franklin and Marshall College
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Affiliation as printed
ETH Zürich
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Affiliation as printed
Department of Media and Communication City University of Hong Kong
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Children’s Institute · University of Rochester
Affiliation as printed
Children's Institute Inc
Department of Psychology University of Rochester
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Affiliation as printed
School of Psychology The University of Queensland
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Affiliation as printed
Department of Psychology and Psychotherapy Witten / Herdecke University
Department of Psychology and Psychotherapy Witten/Herdecke University
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Affiliation as printed
University of Oslo
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Affiliation as printed
IRCCS San Camillo Hospital
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Affiliation as printed
Ashland University
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Affiliation as printed
Bournemouth University
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California State University, East Bay
Affiliation as printed
California State University East Bay
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Affiliation as printed
University of Alabama
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