Due to low levels of item non-response and to maintain trends, all estimates in the Chartbook exclude beneficiaries for whom LDS data are missing for a given measure. Imputations were not performed on the LDS file variables used in the production of the Chartbook, as the LDS variables have already undergone thorough editing, quality control checks, and imputation prior to release. For more detailed information regarding data editing and imputation procedures conducted, please consult the MCBS Methodology Report (see the MCBS Resources section).
There are occasions in which certain categories of variables are excluded from a chart by design. When estimates are presented in charts or tables for these measures, beneficiaries in the excluded categories are not shown in the chart but are still included in the denominator for the estimate, meaning that totals across the categories in the chart may not add up to 100 percent.
Suppression is used in order to protect the confidentiality of Medicare beneficiaries by avoiding the release of information that can be used to identify individual beneficiaries. Estimates with a denominator of less than 50 sample persons or with a numerator of zero sample persons are suppressed in the Chartbook. Suppressed estimates do not appear in the charts; in the tables, suppressed estimates will either appear as asterisks or the suppressed category will be missing from the table altogether. Some estimates are suppressed because they do not meet minimum criteria for reliability, which are explained below.
Statistical Reliability
The Chartbook only displays statistics that meet reliability criteria. This reliability is assessed using two different sets of criteria, depending on the type of estimate. For proportions, the Clopper-Pearson method was used to compute confidence intervals for each estimate. Estimates with a confidence interval whose absolute width is at least 0.30, with a confidence interval whose absolute width is no greater than 0.05, or with a relative confidence interval width of more than 130 percent of the estimate are suppressed in the Chartbook.
For more information: Parker, J. D., M. Talih, D. J. Malec, et al.
National Center for Health Statistics Data Presentation Standards for Proportions.
National Center for Health Statistics. Vital Health Stat 2, no. 175 (2017). Available from:
https://www.cdc.gov/nchs/data/series/sr_02/sr02_175.pdf
For other estimates, relative standard errors (RSEs) are calculated as the standard error of the estimate divided by the estimate itself (percentage), and the result is then converted to a percentage value by multiplying the decimal value by 100. Estimates with a relative standard error of greater than 30 percent are suppressed in this Chartbook because they do not meet the standards of reliability or precision.