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An omnibus approach to assess covariate balance in observational studies using the distance covariance
Adequate baseline covariate balance among groups is critical in observational studies designed to estimate causal effects. Propensity score-based methods are popular ways to achieve covariate balance among groups. Existing methods are not easily generalizable to situations in which covariates of mix...
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Published in: | Statistical methods in medical research 2020-07, Vol.29 (7), p.1846-1866 |
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Main Authors: | , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | Adequate baseline covariate balance among groups is critical in observational studies designed to estimate causal effects. Propensity score-based methods are popular ways to achieve covariate balance among groups. Existing methods are not easily generalizable to situations in which covariates of mixed type are collected nor do they provide a convenient way to compare the overall covariate vector distributions. Instead, covariate balance is assessed at the individual covariate level, thus the potential for increased overall type I error. We propose the use of the distance covariance, developed by Székely and colleagues, as an omnibus test of independence between covariate vectors and study group. We illustrate the advantages of this methodology in simulated data and in a cardiac surgery study designed to assess the impact of preoperative statin therapy on outcomes. |
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ISSN: | 0962-2802 1477-0334 |
DOI: | 10.1177/0962280219878215 |