A non-parametric method that estimates upper and lower bounds for an MR causal effect. The bounds are not the same as confidence intervals and reflect the upper and lower limits of an estimated distribution of causal effects.
For this method to provide a valid causal estimate of the exposure on the outcome, genetic variants must satisfy the MR assumptions, but this method does not require any of the additional MR assumptions. This method can only be used in the situation of binary (or categorical with few levels) exposure, instrumental variable (IV) and outcome. A method for implementing these in Stata has been developed.
References
- Balke A, Pearl J. Bounds on Treatment Effects from Studies with Imperfect Compliance. Journal of the American Statistical Association 1997; 92: 1171-1176.
- Palmer TM, Ramsahai RR, Didelez V, Sheehan NA. Nonparametric bounds for the causal effect in a binary instrumental-variable model. Stata Journal 2011; 11: 345-367.
Other terms in 'One-sample MR methods':
- Generalized Method of Moments (GMM) estimator
- MR with a time-to-event outcome
- Polygenic risk score approach
- Structural Mean Models (SMMs)
- Two-stage least squares (TSLS)
- Two-stage least squares (TSLS) with binary outcomes
- Two-stage predictor substitution estimators
- Two-stage residual inclusion estimators
- Within-family MR