This research uses an advanced statistical technique to expand upon the current understanding of war termination. Specifically, this thesis addressed questions concerning the most relevant factors toward predicting both the outcomes of interstate wars and the winners of intrastate and extra-systemic wars, within the limitations of the available data. Open-source war data from the Correlates of War Project was analyzed using both binary and multinomial logistic regression techniques. While the Correlates of War Project did not necessarily focus its data collection efforts on those variables historically associated with war termination, it did provide a sufficient number of variables with which to demonstrate the applicability of logistic regression techniques to war termination analyses. As a consequence, every significant logistic regression model contains a single relevant variable. For both intrastate and extra-systemic wars, the duration of the conflict was found to be most relevant to predicting the winner. In contrast, the proportion of total casualties borne by a nation in an interstate war was most relevant to predicting the manner in which an interstate war ends. Conclusions drawn from this research and suggestions for future statistical applications to war termination studies were also discussed.
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Paperback. Etat : new. Paperback. This research uses an advanced statistical technique to expand upon the current understanding of war termination. Specifically, this thesis addressed questions concerning the most relevant factors toward predicting both the outcomes of interstate wars and the winners of intrastate and extra-systemic wars, within the limitations of the available data. Open-source war data from the Correlates of War Project was analyzed using both binary and multinomial logistic regression techniques. While the Correlates of War Project did not necessarily focus its data collection efforts on those variables historically associated with war termination, it did provide a sufficient number of variables with which to demonstrate the applicability of logistic regression techniques to war termination analyses. As a consequence, every significant logistic regression model contains a single relevant variable. For both intrastate and extra-systemic wars, the duration of the conflict was found to be most relevant to predicting the winner. In contrast, the proportion of total casualties borne by a nation in an interstate war was most relevant to predicting the manner in which an interstate war ends. Conclusions drawn from this research and suggestions for future statistical applications to war termination studies were also discussed.This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work.This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. N° de réf. du vendeur 9781025087801
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