ASD is a disabling condition. Prospective analysis of consecutively enrolled patients with ASD demonstrated that PT and PI-LL combined with SVA can predict patient disability and provide a guide for patient assessment for appropriate therapeutic decision making. Threshold values for severe disability (ODI > 40) included: PT 22° or more, SVA 47 mm or more, and PI - LL 11° or more.
Our findings demonstrate that, similar to the thoracolumbar spine, the severity of disability increases with positive sagittal malalignment following surgical reconstruction.
Abstract:Researchers using changes in compulsory schooling laws as instruments have typically estimated very high returns to additional schooling that are greater than the corresponding OLS estimates. Given that the first order source of bias in OLS is likely to be upward as more able individuals tend to obtain more education, such high estimates are usually rationalized as reflecting the fact that the group of individuals who are influenced by the law change have particularly high returns to education. That is, the Local Average Treatment Effect (LATE) is larger than the average treatment effect (ATE). However, studies of a 1947 British compulsory schooling law change that impacted about half the relevant population (so the LATE approximates the ATE) have also found very high IV returns to schooling (about 15%), suggesting that the ATE of schooling is greater than OLS estimates would suggest. This constitutes a puzzle: How can the OLS return to schooling be a significantly downward biased estimate of the ATE when the primary source of OLS bias should be upward? We utilize a source of earnings data, the New Earnings Survey Panel Data-set (NESPD), that is superior to the datasets previously used and conclude that there is no such puzzle: the IV estimates are small and much lower than OLS. In fact, there is no evidence of any return for women and the return for men is in the 4-7% range. We do, however, find that men benefit from greater schooling through a reduction in earnings variability.JEL Classification: J30, J31, J24, I20
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.