Faculty

Marc A. Scott

Associate Professor of Educational Statistics

Marc A. Scott

Phone: 212-992-9407
Email:

Dr. Scott's research involves the development of statistical models for longitudinal data. Using latent variable technology, he developed a new class of covariance models for such data, and has used them to examine recent trends in wage inequality. More recent applications include medical histories. He also works on models for longitudinal sequence analysis. In the educational setting, such models examine the influence of the entire pathway (e.g., the timing of educational and employment spells and interruptions to these) on an outcome measure such as wages or degree completion. In current work on low-wage labor markets, such models seek to find similar structure in the career histories and education of workers to identify more and less successful career ladders. This work is a part of a larger project on Service Sector employment at University of Wisconsin's Center on Wisconsin Strategy (COWS).

The assessment of the participation and outcome patterns in postsecondary occupational education was part of the U.S. Department of Education's National Assessment of Vocational Education (NAVE). Dr. Scott has an affiliation with the Institute on Education and the Economy, Teachers College, Columbia University, where that work was centered. More recent work as a fellow at NYU's Institute on Education and Social Policy centers on spatial analyses of school-level test results.

Dr. Scott teaches Multi-Level Models: Growth Curves / Nested Data (E10.2040/41/42), Classification and Clustering (E10.2011), and Biostatistics I & II (E10.2995,2996). Fall 2005, he taught a new Spatial Statistics course (E10.2090). He serves as co-director with Lisa Stulberg of the Interdepartmental Research Studies (IDRS) program; follow this link to website for descriptions of this program and links to course schedules and syllabi. In Fall 2008, Steinhardt launched a new Center for the Promotion of Research Involving Innovative Statistical Methodology (PRIISM) , for which he and Jennifer Hill serve as co-directors.

Education

Links

Grants and Awards

Research

Publications

Presentations

Courses Taught