Nonlinear exposure-outcome relations should not be a barrier to instrumental variable analyses. When the exposure-outcome relation is not linear, either a population-averaged causal effect or the shape of the exposure-outcome relation can be estimated.
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Burgess et al. (2014) studied this question.
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