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  4. PowerMeter - User Friendly Power Analysis for HCI Studies
 
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2026
Conference Paper
Title

PowerMeter - User Friendly Power Analysis for HCI Studies

Abstract
Determining the right sample size for empirical studies is a persistent challenge in human-computer interaction research. Studies with too few participants risk low statistical power and unreliable findings, yet existing tools for power analysis, such as G*Power, are often difficult to use. We present PowerMeter, a user-centered tool that helps researchers estimate appropriate sample sizes for quantitative studies. PowerMeter focuses on usability and interpretability, guiding users through the process of defining key study parameters and understanding the implications of statistical power. In a pilot study (N = 60), we find that participants using PowerMeter produced more accurate sample size estimates and reported higher levels of trust and satisfaction than those using G*Power.
Author(s)
Martius, Florin
Universität Bonn
Struck, Lukas
Universität Bonn
Borgert, Nele
University of Bern
Ortloff, Anna Marie
Universität Bonn
Lenau, Simon
CISPA - Helmholtz Center for Information Security
Schröder, Kay
Hochschule Düsseldorf
Sans-Raimbault, Theo
Universität Bonn
Heinrich, Leonard
Universität Bonn
Smith, Matthew  
Fraunhofer-Institut für Kommunikation, Informationsverarbeitung und Ergonomie FKIE  
Tiefenau, Christian
Universität Bonn
Mainwork
CHI 2026, CHI Conference on Human Factors in Computing Systems. Extended Abstracts  
Conference
Conference on Human Factors in Computing Systems 2026  
Open Access
File(s)
Download (1.2 MB)
Rights
CC BY 4.0: Creative Commons Attribution
DOI
10.1145/3772363.3799267
10.24406/publica-8645
Additional link
Full text
Language
English
Fraunhofer-Institut für Kommunikation, Informationsverarbeitung und Ergonomie FKIE  
Keyword(s)
  • HCI methods

  • power analysis

  • statistical program

  • user study

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