Mean human response curves and associated biomechanical response targets are commonly developed from Post-Mortem Human Subject (PMHS) test data to guide the design of anthropomorphic test devices (ATDs) by providing “target” biomechanical responses to impact. Since differences in anthropometry and physical characteristics within a group of PMHS can result in widely varying response data, the first step in developing target biomechanical responses is typically to normalize the responses to a certain “standard” anthropometry representing the ATD to be designed or evaluated. The normalization procedure should adjust the response data to account for the variation in anthropometry and physical characteristics, and thus should collapse the group of curves closer to a single response so that a mean response can be more accurately established that represents the human response of the “standard” anthropometry selected. Several methods for normalizing PMHS test data can be found in the literature, but there is no consensus as to which is the most effective. In this study, the two most common existing normalization techniques, as well as some newly developed methodologies, were evaluated by applying them to both a side impact PMHS sled test data set, and a lateral and oblique pendulum side impact PMHS data set. The efficacy of the normalization techniques were assessed for each group of common signals by calculating the average percent coefficient of variation (%CV) for timehistory curves, and an analogous measure for forcedeflection curves (%CV_ellipse). Both of these measures provide a quantifiable assessment of the similitude of the group of curves (i.e., the normalization technique resulting in the lowest average %CV value or %CV_ellipse value most effectively collapses the curves). The normalization technique found to consistently perform the best is a newly developed extension of impulse momentumbased normalization in which the stiffness ratio was determined from effective stiffness values calculated from the test data, rather than using characteristic lengths. Utilization of an improved normalization methodology in the development of mean human response curves should prove useful in more accurately characterizing the target human response to aid in the design of more biofidelic dummies.