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Cited by 308Psychometric Methodologies and TestingStatistical Methods and Bayesian InferenceMeta-analysis and systematic reviews

The DOI matches its Crossref record; 40 of the 42 references it cites were found in a registry or an index.

semPower: General power analysis for structural equation models

Open access
Moshagen, Morten, Bader, Martina·2023·Behavior Research Methods
DOI 10.3758/s13428-023-02254-7PMC PMC11522193
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Abstract

Structural equation modeling (SEM) is a widespread and commonly used approach to test substantive hypotheses in the social and behavioral sciences. When performing hypothesis tests, it is vital to rely on a sufficiently large sample size to achieve an adequate degree of statistical power to detect the hypothesized effect. However, applications of SEM rarely consider statistical power in informing sample size considerations or determine the statistical power for the focal hypothesis tests performed. One reason is the difficulty in translating substantive hypotheses into specific effect size values required to perform power analyses, as well as the lack of user-friendly software to automate this process. The present paper presents the second version of the R package semPower which includes comprehensive functionality for various types of power analyses in SEM. Specifically, semPower 2 allows one to perform both analytical and simulated a priori, post hoc, and compromise power analysis for structural equation models with or without latent variables, and also supports multigroup settings and provides user-friendly convenience functions for many common model types (e.g., standard confirmatory factor analysis [CFA] models, regression models, autoregressive moving average [ARMA] models, cross-lagged panel models) to simplify power analyses when a model-based definition of the effect in terms of model parameters is desired.

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Fig. 1 Central and noncentral χ2 distributions, critical χ2 value, and associated decision errors. Note. Central χ2(df) distribution (solid line) and noncentral χ2(df, λ) distributions (dashed lines) with df = 50 and (from top to bottom) non-centrality parameters of λ = 30.25, λ = 46.75, and λ = 62.375. The dotted vertical line indicates a critical value for χc² of 67.50, which corresponds to alpha = .05. The beta-errors are β = .20, β = .03, and β = .003, respectively
Fig. 1 Central and noncentral χ2 distributions, critical χ2 value, and associated decision errors. Note. Central χ2(df) distribution (solid line) and noncentral χ2(df, λ) distributions (dashed lines) with df = 50 and (from top to bottom) non-centrality parameters of λ = 30.25, λ = 46.75, and λ = 62.375. The dotted vertical line indicates a critical value for χc² of 67.50, which corresponds to alpha = .05. The beta-errors are β = .20, β = .03, and β = .003, respectivelyCC BY · PubMed Central
Fig. 2 Statistical power as a function of sample size to detect RMSEA = .05 on 50 df (F0 = 0.125)
Fig. 2 Statistical power as a function of sample size to detect RMSEA = .05 on 50 df (F0 = 0.125)CC BY · PubMed Central

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Cites

Show all 42 references

Research works printed but not linked: 3

  1. Saris, W. E., & Satorra, A. (1993). Power evaluations in structural equation models. In K. A. Bollen & J. S. Long (Eds.), Testing structural equation models (154th ed., pp. 181–204). Sage.
  2. Satorra, A., & Saris, W. E. (1983). The accuracy of a procedure for calculating the power of the likelihood ratio test as used within the LISREL framework. In C. O. Middendorp (Ed.), Sociometric research (pp. 129–190). Sociometric Research Foundation.
  3. Zhang, Z., & Yuan, K.-H. (2018). Practical statistical power analysis using Webpower and R. Isdsa Press. · DOI

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Metadata

Authors
Moshagen, M., & Bader, M.
Affiliations
Universität Ulm (DE)
Corresponding author
Moshagen, Morten
ORCID
Venue
Behavior Research Methods
Publisher
Springer Science and Business Media LLC
Published
2023-11-10
Volume
56
Issue
4
Pages
2901-2922
ISSN
  • 1554-351X (ISSN-L)
  • 1554-3528
DOI
10.3758/s13428-023-02254-7
PMC
PMC11522193
OpenAlex
W4388558341
Cited by
308
References
42
Citations by year
2026: 121 · 2025: 133 · 2024: 50 · 2023: 3
FWCI
56.57
Type
journal article
Language
en
Open access
Licence
Locations
  • Behavior Research Methods (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • OPen Access Repositorium der Universität Ulm (OPARU) (Ulm University) (submittedVersion, cc-by)
Funders
Universität Ulm
Topics
  • Social Sciences › Decision Sciences › Management Science and Operations Research › Psychometric Methodologies and Testing
  • Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
  • Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
Keywords
structural equation modeling, statistical power analysis, sample size determination, a priori power analysis, post hoc power analysis, effect size, multigroup analysis, confirmatory factor analysis, cross-lagged panel model, ARMA models, latent variables
MeSH terms
Latent Class Analysis, Data Interpretation, Statistical, Factor Analysis, Statistical, Humans, Software, Models, Statistical, Sample Size

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