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Bureau of Labor Statistics > Office of Survey Methods Research > Home

Danny Yang

Daniel Yang, Ph.D.

Research Mathematical Statistician Office Of Survey Methods Research

202-691-7530 yang.daniel@bls.gov

Education:

Oregon State University, 2004, M.S., Statistics
Oregon State University, 2012, Ph.D., Statistics

Fields of Interest:

Respondent Burden
Recursive Partitioning Tree Models for Complex Design
Response Propensity
Survey of Occupational Injuries and Illnesses (SOII) Case and Demographic Injury Rate Variance Estimation

Professional Experience:

Research Mathematical Statistician, Bureau of Labor Statistics, 2012-present.
Pre-doctoral Fellow, Kaiser Permanente Center for Health Research, Portland, Oregon, 2005.

Selected Publications and Working Papers:

Lesser, V.M, D. Yang and L. Newton. 2011. Assessing Hunters’ Opinions Based on a Mail and a Mixed-Mode Survey. Human Dimensions of Wildlife, Volume 16, Issue 3, 2011, pp. 1-10.
Lesser, V.M, L. Newton and D. Yang. 2012. Comparing Item Nonresponse across Different Delivery Modes in General Population Surveys. Survey Practice, Vol. 5, Issue 2, 2012.
Yang, D. 2013. Numerical Impact of a Simple Random Subsample on Consumer Spending for Children. In FCSM Proceedings, Federal Committee on Statistical Methodology (FCSM) Research Conference, Concurrent Session I-3: Examining the Impacts of Sample Design: Cost, Bias, Variance and Other Survey Concerns, Washington, DC.
Yang, D., and J. Gonzalez. 2013. Impact of Design Changes on Economic Analyses Project. Working Paper, Consumer Expenditure Surveys, U.S. Bureau of Labor Statistics, Washington, DC.
Yang, D. and D. Toth. 2014. Measuring Impact of Top-Coding on the Utility of Consumer Expenditure Microdata. In JSM Proceedings, American Statistical Association (ASA) Joint Statistical Meetings (JSM), Section on Survey Research Methods, Session 346: Disclosure, Confidentiality, Privacy, Boston, MA. 1171-1184.
Yang, D. and D. Toth. 2015. Assessing the Utility of Top-Coded Consumer Expenditure Survey Data. Working Paper, Presented at the American Statistical Association (ASA) Joint Statistical Meetings (JSM), Government Statistics Section, Session 411: Protecting Privacy While Maximizing the Utility of Government Data: Evaluating Current Approaches and Exploring New Alternatives, Seattle, WA, September 2015.
Yang, D., S. Fricker and J. Eltinge. 2019. Methods for Exploratory Assessment of Consent-to-Link in a Household Survey. Journal of Survey Statistics and Methodology (2019), Volume 7 Issue 1, 118–155.
Yang, D. and D. Toth. 2019. Assessing How a Household Survey Is Perceived by Respondents. In JSM Proceedings, American Statistical Association (ASA) Joint Statistical Meetings (JSM), Government Statistics Section, Session 66: Improving Data Collection: Challenges in Survey Practice, Denver, CO. 3186-3204.

Last Modified Date: August 31, 2022