Precision Standards Guidelines for Reporting MEPSHC Descriptive Statistics
The following statistical standards are applied for tabular estimates that can be obtained from the MEPS website, and are recommended as general rules for researchers analyzing MEPS publicuse file data.
A. Continuous Variables (estimates of means, totals or ratios)
 Number of Sample Persons
 n ≥ 60: Published estimates should be based on an unweighted sample of at least 60 persons for the subgroup of interest.
 Relative Standard Error (RSE = SE/Estimate)
 RSE > .50: Estimate should not be reported or displayed in tables due to extremely large sampling error.
 .30 ≤ RSE ≤ .50: Estimate can be reported but flagged with an * to indicate that its precision is questionable.
 RSE < .30: Estimate is deemed precise and can be reported with no *.
B. Categorical Variables (estimates total counts or percentages)
 Number of Sample Persons
 n ≥ 60^{1}: Published estimates should be based on an unweighted sample of at least 60 persons for the subgroup
represented in the total count (e.g. # children without insurance) or in the denominator of a percentage^{1}.
 Relative Standard Error (RSE = SE/Estimate)
 RSE > .50: Do not report estimate if upper bound of 95% confidence interval for the estimate is > 10%. If upper bound is 10% or less, then it is permissible to report with an *^{2}.
 .30 ≤ RSE ≤ .50: : Estimate can be reported but flagged with an * to indicate that its precision is questionable.
 RSE < .30: Estimate is deemed precise and can be reported with no *.
^{1}For example, the denominator when estimating the percentage of children without
health insurance (# children without insurance/total # of children) is the total # of children in the sample.
^{2}The purpose of this exception is to avoid suppressing all estimates of
characteristics with low estimated prevalence (e.g., less than 10%) due to large RSEs attributable to small denominators.
For example, the RSE for an estimate of 2% with an SE of 1 percentage point is 0.5. In this situation, the upper end of a
95% confidence interval would be around 4% which provides useful information that the prevalence of the characteristic is
fairly uncommon (i.e. likely no higher than 4%). However, if the estimate had been 50% with an RSE of .50, then the
95% confidence interval would span from around 0 to 100. That estimate would clearly be too imprecise to provide any
useful information.
