In early 2008, the Federal Highway Administration issued a task order under the Advanced Quality Systems Indefinite Delivery/Indefinite Quantity Contract for a contractor to quantify the effectiveness of State quality assurance (QA) programs. The objective of the study was to develop, apply, and make recommendations for the use of a procedure that transportation departments could use to quantify and improve the effectiveness of existing quality assurance programs. Based on the knowledge and experience of the research team, four State highway agencies (SHAs) were chosen to participate. An introductory project meeting was held in December 2008, but due to personnel problems, only three agencies participated. The goal of the meeting was to discuss the objectives and scope of the project with State representatives and request their input. The three SHAs agreed to provide QA data from construction projects in their State for the team to analyze. Because sufficient data were not available to accomplish the original task, the scope was modified to use an analysis of acceptance procedures included in the agencies' specifications instead of using actual QA data. In summary, four SHA construction specifications were selected for analysis from three SHAs, two for hot mix asphalt (HMA) pavements and two for portland cement concrete (PCC) pavements. The study shows that either the computer program SPECRISK or computer simulation can be used to analyze the statistical risks of most, if not all, specifications. Both HMA pavement specifications and one of the PCC pavement specifications were amenable to analysis by SPECRISK because they are based on percent within limits as the statistical quality measure. The remaining PCC pavement specification was based on averages and had to be analyzed by computer simulation. Probabilistic Optimization for Profit (Prob. O. Prof) was one of the software programs anticipated to be useful in the analysis. However, it required data that were not available and thus could not be used in the analyses. The report includes analysis of the specifications, particularly the risks involved and recommendations for improving areas that are considered unclear or statistically invalid.