Sharif University of Technology Scientia Iranica 1026-3098 23 2 2016 04 01 Proposing a global sensitivity analysis method for linear models in the presence of correlation among input variables Proposing a global sensitivity analysis method for linear models in the presence of correlation among input variables 399 406 2126 10.24200/sci.2016.2126 EN Y. Daneshbod Dept. of Civil and Environmental Engineering, Shiraz University, Shiraz, Iran M. J. Abedini Dept. of Civil and Environmental Engineering, Shiraz University, Shiraz, Iran 0000-0002-0756-3872 Journal Article 2015 09 16 Sensitivity analysis is considered as an important part of evaluating the performance of mathematical or numerical models. One-factor-at-a-time (OAT) and differential methods are among the most popular sensitivity analysis (SA) schemes employed in the literature. The two major limitations of the above methods are lack of addressing the correlation between model factors and being a local method. Given these limitations, its extensive use among modelers raises concern over the credibility of the associated sensitivity analyses.This paper proposes proof of the inefficiency of the aforementioned methods drawing from experimental designs, and provides a novel technique based on principal component analysis (PCA) to address the issue of the correlation among input factors. In addition, proper guidelines are suggested to handle other conditions. https://scientiairanica.sharif.edu/article_2126_3b92d18aa7a6176dd37d372bc2f1eb71.pdf