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

Ze-wei Ma; Wei-nan Zeng

doi:doi:10.11648/j.ajap.20140303.15

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

Ze-wei Ma, Wei-nan Zeng

Published in American Journal of Applied Psychology (Volume 3, Issue 3)

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

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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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TY  - JOUR
T1  - A Multiple Mediator Model: Power Analysis Based on Monte Carlo Simulation
AU  - Ze-wei Ma
AU  - Wei-nan Zeng
Y1  - 2014/06/20
PY  - 2014
N1  - https://doi.org/10.11648/j.ajap.20140303.15
DO  - 10.11648/j.ajap.20140303.15
T2  - American Journal of Applied Psychology
JF  - American Journal of Applied Psychology
JO  - American Journal of Applied Psychology
SP  - 72
EP  - 79
PB  - Science Publishing Group
SN  - 2328-5672
UR  - https://doi.org/10.11648/j.ajap.20140303.15
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
IS  - 3
ER  -

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Author Information

Ze-wei Ma

Thye Hua Social Work Service Center, Luogang District, Guangzhou 510555, China
Wei-nan Zeng

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

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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

Copy | Download

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

Copy | Download

@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}
}

Copy | Download

TY  - JOUR
T1  - A Multiple Mediator Model: Power Analysis Based on Monte Carlo Simulation
AU  - Ze-wei Ma
AU  - Wei-nan Zeng
Y1  - 2014/06/20
PY  - 2014
N1  - https://doi.org/10.11648/j.ajap.20140303.15
DO  - 10.11648/j.ajap.20140303.15
T2  - American Journal of Applied Psychology
JF  - American Journal of Applied Psychology
JO  - American Journal of Applied Psychology
SP  - 72
EP  - 79
PB  - Science Publishing Group
SN  - 2328-5672
UR  - https://doi.org/10.11648/j.ajap.20140303.15
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
IS  - 3
ER  -

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