The table below may be used to determine standard errors associated with estimates obtained from the National Occupational Exposure Survey (NOES). The table may be used for estimates of numbers of facilities or numbers of employees.
To use the table, first locate the estimated value in the lefthand column and associated value of the multiplier in the right hand column. The value of the standard error is found by multiplying the estimate and multiplier together. Interval estimates may be obtained by multiplying the standard error by two and alternatively adding and subtracting this value from the estimated number of employees or plants. For example, the standard error associated with an estimate of 50,000 would be 50,000 x 0.15, or 7,500. An interval estimate would be between 35,000 and 65,000.
Standard errors associated with low estimated values (less than 500) are greater than 50% of the estimate. Interval estimates for such low estimates should range between 1 and the estimate plus two standard errors. Any estimate whose standard error is greater than 25% of the estimate itself (as when the estimate is less than 8,000) should be considered unreliable and interval estimates should be documented.
Values in the table were obtained by performing nonlinear regression on a set of 792 standard errors computed for different sized estimates from each of the 43 major Standard Industrial Classification (SIC) groups included in the NOES. See Sieber, National Occupational Exposure Survey, Volume II: Sampling Methodology, pages 4549, for an explanation of the calculation of standard errors.



Estimated
Value 
Multiplier 
Estimated
Value 
Multiplier 
50 
0.94 
80,000 
0.13 
100 
0.78 
100,000 
0.12 
200 
0.65 
200,000 
0.10 
300 
0.58 
400,000 
0.08 
500 
0.51 
500,000 
0.08 
700 
0.46 
700,000 
0.07 
1,000 
0.42 
900,000 
0.07 
2,000 
0.35 
1,000,000 
0.07 
5,000 
0.27 
2,000,000 
0.06 
8,000 
0.24 
4,000,000 
0.04 
10,000 
0.23 
5,000,000 
0.04 
12,000 
0.22 
7,000,000 
0.04 
15,000 
0.20 
9,000,000 
0.04 
20,000 
0.19 
10,000,000 
0.01 
40,000 
0.16 
20,000,000 
0.01 
50,000 
0.15 
40,000,000 
0.01 