Government

Students & Educators
Nadja Young 0
Value-added myth busting, Part 4: Value-added models cannot measure growth of students who have missing data or are highly mobile

Students with missing test scores are often highly mobile students and are more likely to be low-achieving students. It is important to include these students in any growth/value-added model to avoid selection bias, which could provide misleading growth estimates to districts, schools and teachers that serve higher populations of these

Students & Educators
Nadja Young 0
Busting myths of education value-added analysis, Part 3: Simple growth measures provide better information to educators.

Welcome to Part 3 of the value-added Myth Busters blog series. I have heard a variation of this many times. “Why shouldn’t educators just use a simple gains approach or a pre- and post-test? They can trust simpler methodologies because they can replicate and understand them more easily.” Simple growth measures

Students & Educators
Nadja Young 0
Busting myths of education value-added analysis, Part 2: It is harder to show growth with high-achieving students

Welcome to Part 2 of the value-added Myth Busters blog series…have you heard this one before? Educators serving high-achieving students are often concerned that their students’ entering achievement level makes it more difficult for them to show growth. “How can my students show growth if they are already earning high

Students & Educators
Nadja Young 0
Busting myths of education value-added analysis, Part 1: You must control for demographics

In the past five years, value-added models have been increasingly adopted by states to support various teaching effectiveness policies. As educators make the paradigm shift from looking at only achievement data to incorporating growth data, many misconceptions have developed. Compounding this issue is the fact that not all value-added and

Fraud & Security Intelligence
Greg Henderson 0
Michigan’s holistic view of fraud is what’s required to combat organized criminal networks

SAS announced yesterday that Michigan will use the SAS Fraud Framework for Government to, initially, combat fraud, waste and abuse in the state’s unemployment insurance and food stamp programs. Those two programs are good focus areas and I’m confident they will lead to the state recovering funds, avoiding losses and

Analytics
Melissa Savage 0
Analytics fuels recommendations in new Department of Transportation innovation handbook

Analytics is a key piece in nearly all 31 recommendations outlined in The Innovative DOT: A Handbook of Policy and Practice.  Crafted by the State Smart Transportation Initiative, in partnership with Smart Growth America, the handbook provides 31 recommendations for state transportation officials looking for ways to increase efficiencies and

Analytics | Fraud & Security Intelligence
Carl Hammersburg 0
Employee misclassification: Will the last employee please turn off the lights?

Independent contractor.  Two very simple words that have a dramatic impact on businesses, workers, and government programs.  While most people have a basic understanding of the term, they often have very little understanding of the laws governing it, which vary significantly program by program and state by state.  This has

Analytics | Fraud & Security Intelligence
Greg Henderson 0
"Financial fraud is the dominant crime of this millennium"

Several weeks ago, South Carolina was the victim of what some experts believe to be the largest cyber-attack against a state tax department in history. Approximately 3.6 million personal South Carolina income tax returns were exposed, and nearly 657,000 businesses compromised, in an international hacking attack. Coincidentally, SAS and the SC

Analytics
John Stultz 0
Federal policy on improper payments spurs need for high performance analytics

Recently, top executives from SAS gathered in Washington, DC with customers and other interested parties to discuss the potential impact of "big data" and high-performance analytics on the U.S. government. Topics included cyber-attack strategies, health care, bio-surveillance, border security and of course, fraud and improper payments. On the heels of

1 13 14 15 16 17 18