Publications
- Irimata KE, Scanlon PJ, Moriarity C, Cai B, Beresovsky B, Wei R. Findings from RANDS 7. DRM Research Memo. 2023-04E [PDF – 1 MB]
- Irimata KE, He Y, Parsons VL, Shin H-C, Zhang G. Calibration weighting methods for the National Center for Health Statistics Research and Development Survey [PDF – 1 MB]. National Center for Health Statistics. Vital Health Stat 2(199). 2023.
- He Y, Zhang G. Multiple imputation analysis of missing complex survey data using SAS®: A brief overview and an example based on the Research and Development Survey (RANDS). The Survey Statistician 87. 2023.
- Irimata KE, Pleis JR, Heslin KC, He Y. Reduced access to preventive care due to the COVID-19 pandemic, by chronic disease status and race and Hispanic origin, United States, 2020–2021. Public Health Rep 0(0):1-8. DOI: 1177/00333549221138855.
- Shin H-C, Parker J, Parsons V, He Y, Irimata K, Cai B, Beresovsky V. Propensity-score adjusted estimates for selected health outcomes from the Research and Development Survey. National Center for Health Statistics. Vital Health Stat 2(196). 2022. DOI: https://dx.doi.org/10.15620/cdc:121708.
- Li Y, Irimata K, He Y, Parker J. Variable inclusion strategies through directed acyclic graphs to adjust health surveys subject to selection bias for producing national estimates. J Off Stat 38(3):875–900. 2022.
- Irimata KE, Scanlon PJ. The Research and Development Survey (RANDS) during COVID-19. Stat J IAOS 38(1):13–21. 2022.
- Irimata KE, He Y, Cai B, Shin H-C, Parsons VL, Parker JD. Comparison of quarterly and yearly calibration data for propensity score adjusted web survey estimates. Surv Methods Insights Field. 2020. DOI: 10.13094/SMIF-2020-00018.
- Parker J, Miller K, He Y, Scanlon P, Cai B, Shin H-C, et al. Overview and initial results of the National Center for Health Statistics’ Research and Development Survey. Stat J IAOS 36(4):1199–1211. 2020. DOI: 3233/SJI-200678.
- He Y, Cai B, Shin H-C, Beresovsky V, Parsons V, Irimata K, et al. The National Center for Health Statistics’ 2015 and 2016 Research and Development Surveys. National Center for Health Statistics. Vital Health Stat 1(64). 2020.
- Scanlon P. Cognitive evaluation of the National Center for Health Statistics’ 2018 Research and Development Survey. National Center for Health Statistics Q-Bank. 2020.
- Scanlon P. The effects of embedding closed-ended cognitive probes in a web survey on survey response. Field Methods 31(4):328–43. 2019. DOI: 10.1177/1525822X19871546.
- Scanlon P. Using targeted embedded probes to quantify cognitive interviewing findings. In: Beatty PC, Collins D, Kaye L, Padilla JL, Willis GB, Wilmot A, editors. Advances in questionnaire design, development, evaluation, and testing. Hoboken, NJ: John Wiley & Sons, 427–50. 2019. DOI: 10.1002/9781119263685.ch17.
- Beresovsky V. Comparing random and nonrandom samples using model-implied randomization. In: 2018 Proceedings of the Federal Committee on Statistical Methodology Research Conference. Washington, DC: Federal Committee on Statistical Methodology. 2018.
- He Y, Shin H-C, Cai B, Beresovsky V, Scanlon P, Parsons V, et al. The utility of using web surveys to provide official estimates for major health outcomes: A pilot study. In: 2018 Statistics Canada International Methodology Symposium Proceedings. Ottawa, Canada: Statistics Canada. 2018.
- Scanlon P. Cognitive evaluation of the 2015–2016 National Center for Health Statistics’ Research and Development Survey. National Center for Health Statistics Q-Bank. 2017.
- Beresovsky V. Imputation classes as a framework for inferences from nonrandom samples. In: 2017 Proceedings of the Joint Statistical Meetings. Alexandria, VA: American Statistical Association, 2918–32. 2017.
- Singh AC, Beresovsky V, Ye C. Estimation from purposive samples with the aid of probability supplements but without data on the study variable. In: 2017 Proceedings of the Joint Statistical Meetings. Alexandria, VA: American Statistical Association, 3324–45. 2017.