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A Multiple Mediator Model: Power Analysis Based on Monte Carlo Simulation

Received: 10 May 2014     Accepted: 26 May 2014     Published: 20 June 2014
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Abstract

Most of the applied psychological researchers usually conduct studies requiring application of advanced mediation models, such as multiple mediator models. However, in designing research, most of the applied researchers largely ignore the statistical power of their studies. As a result, power analyses are ignored when researchers report their results. It is well recognized that low power is one possible reason for no statistically significant result being identified in a study. Moreover, studies with low statistical power have been labeled “scientifically useless”. The current study describes how to apply Monte Carlo simulation to test the type I error rates and statistical power of mediating effects in a multiple mediator model. Findings from the current simulation study indicated that the effect sizes of mediating effects and sample sizes were two important factors influencing type I error rates of indirect effects in a multiple mediator model. Furthermore, the requirement of sample size and desired power level were strongly depended on the effect size of the indirect effect.

Published in American Journal of Applied Psychology (Volume 3, Issue 3)
DOI 10.11648/j.ajap.20140303.15
Page(s) 72-79
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2014. Published by Science Publishing Group

Keywords

Mediation, Multiple Mediator Models, Statistical Power, Monte Carlo Simulation, Mplus

References
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Cite This Article
  • APA Style

    Ze-wei Ma, Wei-nan Zeng. (2014). A Multiple Mediator Model: Power Analysis Based on Monte Carlo Simulation. American Journal of Applied Psychology, 3(3), 72-79. https://doi.org/10.11648/j.ajap.20140303.15

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    ACS Style

    Ze-wei Ma; Wei-nan Zeng. A Multiple Mediator Model: Power Analysis Based on Monte Carlo Simulation. Am. J. Appl. Psychol. 2014, 3(3), 72-79. doi: 10.11648/j.ajap.20140303.15

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    AMA Style

    Ze-wei Ma, Wei-nan Zeng. A Multiple Mediator Model: Power Analysis Based on Monte Carlo Simulation. Am J Appl Psychol. 2014;3(3):72-79. doi: 10.11648/j.ajap.20140303.15

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  • @article{10.11648/j.ajap.20140303.15,
      author = {Ze-wei Ma and Wei-nan Zeng},
      title = {A Multiple Mediator Model: Power Analysis Based on Monte Carlo Simulation},
      journal = {American Journal of Applied Psychology},
      volume = {3},
      number = {3},
      pages = {72-79},
      doi = {10.11648/j.ajap.20140303.15},
      url = {https://doi.org/10.11648/j.ajap.20140303.15},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajap.20140303.15},
      abstract = {Most of the applied psychological researchers usually conduct studies requiring application of advanced mediation models, such as multiple mediator models. However, in designing research, most of the applied researchers largely ignore the statistical power of their studies. As a result, power analyses are ignored when researchers report their results. It is well recognized that low power is one possible reason for no statistically significant result being identified in a study. Moreover, studies with low statistical power have been labeled “scientifically useless”. The current study describes how to apply Monte Carlo simulation to test the type I error rates and statistical power of mediating effects in a multiple mediator model. Findings from the current simulation study indicated that the effect sizes of mediating effects and sample sizes were two important factors influencing type I error rates of indirect effects in a multiple mediator model. Furthermore, the requirement of sample size and desired power level were strongly depended on the effect size of the indirect effect.},
     year = {2014}
    }
    

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    T1  - A Multiple Mediator Model: Power Analysis Based on Monte Carlo Simulation
    AU  - Ze-wei Ma
    AU  - Wei-nan Zeng
    Y1  - 2014/06/20
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    JF  - American Journal of Applied Psychology
    JO  - American Journal of Applied Psychology
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    AB  - Most of the applied psychological researchers usually conduct studies requiring application of advanced mediation models, such as multiple mediator models. However, in designing research, most of the applied researchers largely ignore the statistical power of their studies. As a result, power analyses are ignored when researchers report their results. It is well recognized that low power is one possible reason for no statistically significant result being identified in a study. Moreover, studies with low statistical power have been labeled “scientifically useless”. The current study describes how to apply Monte Carlo simulation to test the type I error rates and statistical power of mediating effects in a multiple mediator model. Findings from the current simulation study indicated that the effect sizes of mediating effects and sample sizes were two important factors influencing type I error rates of indirect effects in a multiple mediator model. Furthermore, the requirement of sample size and desired power level were strongly depended on the effect size of the indirect effect.
    VL  - 3
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Author Information
  • Thye Hua Social Work Service Center, Luogang District, Guangzhou 510555, China

  • Department of Psychology, School of Humanities and Management, Guangdong Medical College, Dongguan 523808, China

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