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- Data analysis
- Quantitative evaluations
- Randomized controlled trials
- Experimental and quasi-experimental study design
- Statistical methodology
- Hierarchical linear modeling
- Early Childhood
- Child Welfare
- Literacy and Numeracy
- School Choice and Charters
- Strengthening and Disseminating Research
- Labor: Strengthening and Disseminating Research
- Training and Re-employment
- Child Welfare
- Human Services
Natalya Verbitsky-Savitz has experience in designing, conducting, and reporting on the results of experimental and quasi-experimental policy evaluation studies, as well as observational studies in K–12 education, early childhood and child welfare, labor, and other fields.
Verbitsky-Savitz has worked extensively on designing multisite and cluster-randomized studies and analyzing data in clustered settings. As a technical adviser and reviewer on a contract for the U.S. Department of Education’s Institute of Education Sciences, she provides analytic and technical support by reviewing plans and reports produced by the Regional Educational Laboratories. As a certified reviewer and deputy methodologist for the What Works Clearinghouse, she leads a team that reviews, assesses, and rates the rigor of studies that evaluate the effectiveness of educational programs; she also writes reports summarizing the extent of evidence about the effectiveness of various interventions. She is currently the project director and co-principal investigator of a rigorous, mixed-methods evaluation of multifaceted, scalable, community-based initiatives to combat and mitigate the effects of adverse childhood experiences in five communities in Washington State.
Verbitsky-Savitz, who joined Mathematica in 2007, is a member of the American Statistical Association, Institute of Mathematical Statistics, and Association for Public Policy Analysis and Management. She holds a Ph.D. in statistics from the University of Michigan.
National Research Council Assessment of Research Doctorate Programs
Mathematica conducted the 2006 National Research Council assessment of doctoral research programs, which gathered information about doctoral programs in more than 60 areas of study in American universities.
Evaluating Community-Based Family Support Networks to Reduce Adverse Childhood Experiences
Mathematica is conducting a rigorous, mixed-method evaluation of multifaceted, scalable community-based initiatives in five Washington state communities that seek to prevent adverse childhood experiences.
New Study Shows Communities Can Reduce the Effects of Adverse Childhood Experiences
A new study commissioned by the Adverse Childhood Experiences Public-Private Initiative (APPI) of Washington state finds that communities can create effective, local strategies that reduce the long-term social, emotional and physical problems related to abuse, neglect and other Adverse Childhood Experiences...