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In this paper, we investigate the use of the contribution to the sample mean plot (CSM plot) as a graphical tool for sensitivity analysis (SA) of computational models. We first provide an exact formula that links, for each uncertain model inputXj, the CSM plotCj(·) with the first-order variance-based sensitivity indexSj. We then build a new estimate forSjusing polynomial regression of the CSM plot. This estimation procedure allows the computation ofSjfromgiven data, without any SA-specific design of experiment. Numerical results show that this newSjestimate is efficient for large sample sizes, but that at small sample sizes it does not compare well with otherSjestimation techniques based on given data, such as the effective algorithm for computing global sensitivity indices method or metamodel-based approaches. [ABSTRACT FROM PUBLISHER]