Abstract
Mendelian randomization, which is instrumental variable analysis using genetic variants as instruments, is an increasingly popular method of making causal inferences from observational studies. In order to design efficient Mendelian randomization studies, it is essential to calculate the sample sizes required. We present formulas for calculating the power of a Mendelian randomization study using one genetic instrument to detect an effect of a given size, and the minimum sample size required to detect effects for given levels of significance and power, using asymptotic statistical theory. We apply the formulas to some example data and compare the results with those from simulation methods. Power and sample size calculations using these formulas should be more straightforward to carry out than simulation approaches. These formulas make explicit that the sample size needed for Mendelian randomization study is inversely proportional to the square of the correlation between the genetic instrument and the exposure and proportional to the residual variance of the outcome after removing the effect of the exposure, as well as inversely proportional to the square of the effect size.
Keywords
Affiliated Institutions
Related Publications
The many weak instruments problem and Mendelian randomization
Instrumental variable estimates of causal effects can be biased when using many instruments that are only weakly associated with the exposure. We describe several techniques to ...
Calculating statistical power in Mendelian randomization studies
In Mendelian randomization (MR) studies, where genetic variants are used as proxy measures for an exposure trait of interest, obtaining adequate statistical power is frequently ...
Mendelian Randomization Analysis With Multiple Genetic Variants Using Summarized Data
ABSTRACT Genome‐wide association studies, which typically report regression coefficients summarizing the associations of many genetic variants with various traits, are potential...
Detection of widespread horizontal pleiotropy in causal relationships inferred from Mendelian randomization between complex traits and diseases
Horizontal pleiotropy occurs when the variant has an effect on disease outside of its effect on the exposure in Mendelian randomization (MR). Violation of the ‘no horizontal ple...
Mendelian Randomization in the Era of Genomewide Association Studies
Abstract Background: Observational epidemiology has been instrumental in identifying modifiable causes of common diseases, and, in turn, substantially impacting public health. S...
Publication Info
- Year
- 2013
- Type
- article
- Volume
- 42
- Issue
- 4
- Pages
- 1157-1163
- Citations
- 178
- Access
- Closed
External Links
Social Impact
Social media, news, blog, policy document mentions
Citation Metrics
Cite This
Identifiers
- DOI
- 10.1093/ije/dyt110