The Center for Statistical Research & Methodology focuses on applying and developing new methods in the following seven areas of statistical research.
Missing Data & Observational Data Modeling
Missing data and observational data modeling methods are used to compensate when some or all of the data are not captured for some responding units.
Record Linkage & Machine Learning
Record linkage and machine learning methods are used for matching or linking records among various data sets.
Small Area Estimation
Small area estimation methods provide reliable data products for finer geographic levels and subpopulations when sample sizes for these levels are insufficient.
Sampling Estimation & Survey Inference
Sampling estimation and survey inference methods are used for taking sample data and making valid inferences about populations of people or businesses.
Time Series & Seasonal Adjustment
Seasonal adjustment methods are used to monitor activity over time and to remove a component of a time series that reveals a seasonal effect in the data.
Experimentation, Prediction, & Modeling
Experimentation, prediction, and modeling methods are used to build models and design experiments to answer questions related to testing.