Mathematica has launched a new five-year descriptive study of Early Head Start, the Early Head Start Family and Child Experiences Survey (Baby FACES 2018), to guide program technical assistance, management, and policy.
- Early childhood education
- Statistical methods
- Large-scale data set analysis
- Early Childhood
- Child Development
- Data Analytics
Yange Xue has experience in child development and early childhood education evaluations, including assessments of programs for disadvantaged and at-risk children and families. She has expertise in advanced statistical methodologies and extensive experience in leading and conducting secondary data analyses and designing and implementing complex analyses of large-scale data sets.
Xue’s research has included some of Mathematica’s signature studies in early education, including the First 5 LA/Los Angeles Universal Preschool Child Outcomes Study, the Head Start Family and Child Experiences Survey, the Early Head Start Family and Child Experiences Survey (Baby FACES) 2009, and the Measurement Development Quality of Caregiver-Child Interactions for Infants and Toddlers project. She is currently a co-principal investigator for Baby FACES 2017, a five-year descriptive study of Early Head Start programs and families. She also leads the data analysis task for the Early Childhood Development Secondary Data Analysis Project, a study designed to expand the knowledge base of early childhood development and programs, and First 5 LA Comprehensive Professional Development Evaluation project, a longitudinal evaluation of six professional development programs for early childhood educators.
Xue, who joined Mathematica in 2007, is a peer reviewer for numerous publications, including the American Educational Research Journal, Child Development, Early Childhood Research Quarterly, and the Journal of Emotional and Behavioral Disorders. She holds a Ph.D. in early childhood education from the University of Michigan.
Early Head Start Family and Child Experiences Survey: Baby FACES 2018
Professional Development Tools for Improving Quality of Infant and Toddler Care (Q-CCIIT PD Tools)
Following on Mathematica's successful projects to develop and test a measure of the quality of caregiver-child interaction for infants and toddlers (Q-CCIIT), this work improves upon the quality of care by providing caregivers with strategies and tools via an interactive website.
Early Head Start Family and Child Experiences Survey (Baby FACES)
The Early Head Start Family and Child Experiences Survey (Baby FACES) is designed to be a rich source of data describing the experiences of children and their families in Early Head Start.
Early Head Start Research and Evaluation
The program promotes learning and the parenting that supports it within the first three years of life. Participating children performed significantly better in cognitive, language, and social-emotional development than their peers who did not participate.
Universal Preschool Child Outcomes Study (UPCOS)
The Los Angeles Universal Preschool (LAUP) was created to increase the number of preschool slots available in the most underserved Los Angeles' communities. Since 2007, Mathematica has conducted this study to provide descriptive information about the diverse population LAUP serves.