The important features of the sample design employed are its use of stratified random sampling with a Neyman allocation and a ratio estimator. Because these characteristics are highly correlated with an establishment's number and rate of recorded injuries and illnesses, stratified sampling provides greater precision and, thus, results in a smaller sample size than simple random sampling. The Neyman allocation produces the minimum sample size which will provide an estimate with a fixed sampling variance. The certainty strata are usually the size groups with 100 employees or more. The precision of the sample is further improved, hence permitting a reduction in sample size, by using the ratio estimator which in turn uses employment data that are correlated with the characteristics which are to be measured.
States publish industry data at less detailed levels.
The selection of the cases involving days away from work varies by sampled establishment. For each sample unit, an expected number of cases involving days away from work is calculated based on the industry and size class in which that establishment resides. For those establishments with an expected case load less than or equal to 20, the employer is requested to provide case information for all cases involving days away from work occurring in the survey year.