Logistic and Multiple Regression: A Two-Pronged Approach to Accurately Estimate Cost Growth in Major DoD Weapon Systems
Date of Award
Master of Science in Cost Analysis
Department of Mathematics and Statistics
Edward D. White, PhD
This research confirms the usefulness of the logistic and multiple regression two-step procedure for assessing cost growth in major DoD weapon systems. We compile programmatic data from the Selected Acquisition Reports (SARs) between 1990 and 2002 for programs covering all defense departments. Our analysis concentrates on cost growth in the procurement appropriations of the Engineering and Manufacturing Development phase of acquisitions. We investigate the use of logistic regression in cost growth analysis to predict whether or not cost growth will occur in a program. If applicable, multiple regression is implemented to predict how much cost growth will occur. Our study focuses on the estimating and support SAR cost variance categories within the procurement appropriations. We study each of these categories individually for significant cost growth characteristics and develop predictive models for each.
DTIC Accession Number
Rossetti, Matthew B., "Logistic and Multiple Regression: A Two-Pronged Approach to Accurately Estimate Cost Growth in Major DoD Weapon Systems" (2004). Theses and Dissertations. 3964.