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Sample size determination for mediation analysis of longitudinal data

Overview of attention for article published in BMC Medical Research Methodology, March 2018
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (76th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (55th percentile)

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Title
Sample size determination for mediation analysis of longitudinal data
Published in
BMC Medical Research Methodology, March 2018
DOI 10.1186/s12874-018-0473-2
Pubmed ID
Authors

Haitao Pan, Suyu Liu, Danmin Miao, Ying Yuan

Abstract

Sample size planning for longitudinal data is crucial when designing mediation studies because sufficient statistical power is not only required in grant applications and peer-reviewed publications, but is essential to reliable research results. However, sample size determination is not straightforward for mediation analysis of longitudinal design. To facilitate planning the sample size for longitudinal mediation studies with a multilevel mediation model, this article provides the sample size required to achieve 80% power by simulations under various sizes of the mediation effect, within-subject correlations and numbers of repeated measures. The sample size calculation is based on three commonly used mediation tests: Sobel's method, distribution of product method and the bootstrap method. Among the three methods of testing the mediation effects, Sobel's method required the largest sample size to achieve 80% power. Bootstrapping and the distribution of the product method performed similarly and were more powerful than Sobel's method, as reflected by the relatively smaller sample sizes. For all three methods, the sample size required to achieve 80% power depended on the value of the ICC (i.e., within-subject correlation). A larger value of ICC typically required a larger sample size to achieve 80% power. Simulation results also illustrated the advantage of the longitudinal study design. The sample size tables for most encountered scenarios in practice have also been published for convenient use. Extensive simulations study showed that the distribution of the product method and bootstrapping method have superior performance to the Sobel's method, but the product method was recommended to use in practice in terms of less computation time load compared to the bootstrapping method. A R package has been developed for the product method of sample size determination in mediation longitudinal study design.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 238 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 238 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 45 19%
Researcher 36 15%
Student > Master 21 9%
Student > Doctoral Student 20 8%
Professor 13 5%
Other 40 17%
Unknown 63 26%
Readers by discipline Count As %
Psychology 70 29%
Medicine and Dentistry 19 8%
Social Sciences 12 5%
Business, Management and Accounting 9 4%
Neuroscience 7 3%
Other 34 14%
Unknown 87 37%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 9. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 31 March 2018.
All research outputs
#3,780,251
of 23,031,582 outputs
Outputs from BMC Medical Research Methodology
#602
of 2,030 outputs
Outputs of similar age
#75,622
of 330,033 outputs
Outputs of similar age from BMC Medical Research Methodology
#8
of 18 outputs
Altmetric has tracked 23,031,582 research outputs across all sources so far. Compared to these this one has done well and is in the 83rd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,030 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.2. This one has gotten more attention than average, scoring higher than 69% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 330,033 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 76% of its contemporaries.
We're also able to compare this research output to 18 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 55% of its contemporaries.