What question did this study set out to answer?

To derive an analytical framework and user-friendly software tool for calculating statistical power in Mendelian randomization studies involving continuous variables.

October 23, 2012International Journal of EpidemiologyOpen Access

Calculating statistical power in Mendelian randomization studies

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To derive an analytical framework and user-friendly software tool for calculating statistical power in Mendelian randomization studies involving continuous variables.
Applied asymptotic statistical theory to continuous variables using a single instrument or multi-SNP genetic score.
Derived power equations for two-stage least squares (2SLS) regression using the test statistic's non-centrality parameter (NCP).
Benchmarked analytical NCP power calculations against published simulation estimates and implemented the method in an open-access web application.
Demonstrated that statistical power for a given sample size is determined by the exposure variance explained by the genetic instrument and the true causal effect size.
Showed theoretical NCP-based power calculations closely match empirical power estimates derived from computer simulations.
Provided general closed-form equations and an interactive web tool to calculate power for 2SLS Mendelian randomization analyses.

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Implication

Methodological study reveals an analytical power calculation for Mendelian randomization, highlighting simple parameter-based estimation without simulations.

Cite This Study

Brion et al. (2012) studied this question.

synapsesocial.com/papers/69d56fb475589c71d767dab9 https://doi.org/10.1093/ije/dyt179

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Implication

Methodological study reveals an analytical power calculation for Mendelian randomization, highlighting simple parameter-based estimation without simulations.

Calculating statistical power in Mendelian randomization studies

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Discussion

Implication

Cite This Study

Calculating statistical power in Mendelian randomization studies

Key Points

Discussion

Implication

Cite This Study

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