A relative standard error (RSE) greater than 30% was used to identify unreliable estimates. The RSE is defined as the ratio of the standard error of the estimate divided by the estimate multiplied by 100 [RSE = 100 x SE(b) / |b|, which is similar to Coefficient of Variation (CV) = SD(b) / |b|, ].
- Klein (2002): Healthy People 2010 Criteria for Data Suppression (pdf)
- Parker(2017): National Center for Health Statistics data presentation standards for proportions (on page 3: relative CI width calculation and 130% cut-point)
National counts or estimates determined to be unstable are indicated with a footnote in the tables. Fatal injuries were identified as unstable if the number of deaths was <20 or the coefficient of variation (CV) was >30%, where CV = (SE / number of deaths) × 100. Nonfatal injuries were identified as unstable if the national estimate was <1,200, the number of sample cases used was <20, or CV was >30%, where CV = (SE / national estimate) × 100.
Why are rates based on fewer than 20 cases marked as being unreliable?
by NY State Department of Health: Data Sources and Tools - Chronic Diseases and Conditions
Example of a NHIS article (Variance Estimation and Significance Testing)
"... Standard errors are shown for all percentages in the tables (but not for the frequencies). Estimates with relative standard errors (RSE) of greater than 30% and less than or equal to 50% are considered statistically unreliable and are indicated with an asterisk (*). Estimates with a relative standard error greater than 50% are indicated with a dagger (†) and the estimates are not shown..."
More about reliability
- Singh (2004) "A generalization of the Coefficient of variation with application to suppression of imprecise estimates "
- The National Electronic Injury Surveillance System "A tool for research"
- Precision of measurement by A New View of Statistics
- CV by Wikipedia
- Assessing Product Reliability by Engineering Statistics Handbook
- Reliability by the Research Methods Knowledge Base
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