Identification and Estimation of the Bi-Directional MR with Some Invalid Instruments
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Abstract (arXiv)
We consider the challenging problem of estimating causal effects from purely observational data in the bi-directional Mendelian randomization (MR), where some invalid instruments, as well as unmeasured confounding, usually exist. To address this problem, most existing methods attempt to find proper valid instrumental variables (IVs) for the target causal effect by expert knowledge or by assuming that the causal model is a one-directional MR model. As such, in this paper, we first theoretically investigate the identification of the bi-directional MR from observational data. In particular, we provide necessary and sufficient conditions under which valid IV sets are correctly identified such that the bi-directional MR model is identifiable, including the causal directions of a pair of phenotypes (i.e., the treatment and outcome). Moreover, based on the identification theory, we develop a cluster fusion-like method to discover valid IV sets and estimate the causal effects of interest. We theoretically demonstrate the correctness of the proposed algorithm. Experimental results show the effectiveness of our method for estimating causal effects in bi-directional MR.
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References · 7
- 2014From Ordinary Differential Equations to Structural Causal Models: the deterministic casecited by 41
- 2014Instrumental Variables Estimation with Some Invalid Instruments and its Application to Mendelian Randomizationcited by 22
- 2020Valid Causal Inference with (Some) Invalid Instrumentscited by 19
- 2022Discovering Ancestral Instrumental Variables for Causal Inference from Observational Datacited by 7
- 2016Identification and Model Testing in Linear Structural Equation Models using Auxiliary Variablescited by 6
- 2013Semi-Instrumental Variables: A Test for Instrument Admissibilitycited by 5
- 2022A Focusing Framework for Testing Bi-Directional Causal Effects with GWAS Summary Datacited by 1
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