COWORKER DOSE MODELI

Arjun Makhijani, SC&A

Advisory Board on Radiation and Worke

Idaho Falls, Idaho

July 16–17, 2013
I. BACKGROUND

• ORAUT‐RPRT‐0053 discusses methods for developing coworker models. S

are recommended to decide if a single coworker model is appropriate for a site, or if separate coworker models are necessary for different sub‐grou(strata).

•• Several ORAUT documents are based on the analytical methods proposed 

0053. These documents compare coworker models for construction trade

(CTWs) and non‐construction trades workers (NCWs) at the Savannah Rive

•

– ORAUT‐RPRT‐0055, A Comparison of Exotic Trivalent Radionuclide Co

Models at the Savannah River Site, July 2012

– ORAUT‐RPRT‐0056, A Comparison of Neptunium Coworker Models at 

River Site, August 2012

– ORAUT‐RPRT‐0058, A Comparison of Mixed Fission and Activation Pro

Coworker Models at the Savannah River Site, September 2012.

•• This presentation includes examples drawn from our review of these docu

•
II. DATA ISSUES

A. SAMPLING PROTOCOL ISSUE (Findin

• Strata comparisons are valid only when the sampling protocols 

same.

• Issue applies to datasets reduced using the One Person‐One Sa

(OPOS) procedure and to raw datasets of samples.

• If sampling protocols differ, valid statistical comparisons canno

• Example: If monitoring is incident‐driven for one group of wor

for the other, the hypothesis tests do not provide a valid comp

• NIOSH states in RPRT‐0056 and RPRT‐0058:

CTWs are potentially subject to different bioassay practices than otheCTWs, many of whom are contractors, commonly submit bioassay sa

suspected uptakes and at the completion of jobs.

This is in contrast to other workers, especially those employed directl

prime contractor, who are more likely to be on a routine bioassay pro

addition to submitting bioassay samples after suspected uptakes.
B. REPRESENTATIVENESS AND COMPLET

(Finding 2)

• The completeness and representativeness of the data available for coworker m

addressed in ORAUT‐RPRT‐0053. If the unmonitored workers are from a differ

population, the applicability of a coworker model derived from monitored cow

be in question.

• Characteristics of monitored and unmonitored populations should be the same

exposure potential of the monitored versus unmonitored workers needs to bdemonstrated rather than assumed.

• The methods proposed in ORAUT‐RPRT‐0053 for analyzing the coworker datas

verification that:

– The available coworker data are representative of all groups of workers

– The manner of use of the data is claimant favorable for the specific datase

the method is applied

A sound statistical methodology is subject to these two important caveats.

• To this end, it is necessary to examine subgroups of CTWs. Data for the cowo

must be representative of these groups, and there must be sufficient data fo

comparisons with other monitored workers.
C. NUMBER OF STRATA (Recommendati

• NIOSH has not made comparisons of CTW subgro

• Analysis of SRS CTWs by job type and by area of w

(SC&A 2010a, 2010b) indicates that subgroups of C

have unique distributions of exposure and are not 

same distribution as NCWs or other CTW subgroup

• Multiple pairwise comparisons would be required 

CTW analysis. Sufficient data (at least 30 samples 

category) would be required in each job/area cate

which a coworker model is to be constructed. The 

sufficient data for such comparisons.
D. WORKERS CHANGING JOBS (Findin

• The statistical tests for comparing two strata require that the s

each group be independent.

• If a worker in one group is exposed to radionuclides with long r

the body and then changes jobs and becomes part of the othe

the same period, the OPOS values are correlated for this worke

that OPOS aggregation periods can be as long as 3 years.)

• This correlation not only violates the assumptions of the tests, 

creates a bias toward a decision of “No Difference” between th

groups. If CTW and NCW are being compared, it is essential th

designation has not changed during the period of OPOS aggreg

• NIOSH has not investigated whether changes of workers from o

to another occurred during the period of OPOS aggregation ansuch data are to be handled.
III. METHODOLOGICAL ISSUES

A. POWER CONCERNS (Finding 8)

• NIOSH has not provided any measure of the power of the hypo

procedures to detect differences within the worker population

deficiency should be corrected before the tests are adopted as appropriate procedure for coworker models.

• Accepting the null hypothesis could often be very claimant unf

the available data do not provide adequate power for the test.

• NIOSH has stated that 30 samples in each strata is sufficient fo

comparison. We investigated this issue further during our reviSRS application documents noted above. The following very ge

results are reported in our review of the neptunium coworker 

• Table 1 and Figure 1 show results of simulations performed to 

power of the WRS test when using 30 samples to compare logn

distributions which differ by a factor of 2.73. The samples inclunondetects. The GSDs are assumed the same for the two distrSimulation was conducted using Crystal Ball.
A. POWER CONCERNS (Finding 8 ‐ cont

• Results: Type 2 error rates can be very high (15–35%) when using the 95% co

(α=0.05) if the GSDs exceed 4. If the confidence level is reduced to 90% (α=0.

error rate is maintained below 20% up to a GSD of 6. If the confidence level is 

the Type 2 error rate maintained is below 10%.

• Overall, SC&A concludes that the NIOSH method of determining that there a

significant differences based on the available data would often lead to very c

unfavorable results.

SIMULATION RESULTS

Table 1. Type 2 Error Rate of WRS Test using 30 Samples from Two Lognormal Distribution

LN(1,1)

GSD

α 6 5 4 3 2

0.05 0.35 0.27 0.16 0.04 <0.001

0.10 0.22 0.16 0.09 0.02 <0.0010.20 0.11 0.07 0.04 0.006 <0.0010.25 0.09 0.05 0.02 0.003 <0.001

n1=n2=30, 24% nondetects, and GM2/GM1 = 2.73Shaded region of table has Type 2 Error rate ≤10%
Figure 1. Type 2 Error Rate of WRS Test using 30 Samples fro

Two Lognormal Distributions: LN(0,1) and LN(1,1)
B. SMALL SAMPLE SIZES (Finding 6

• Power of the statistical tests to detect differences given the limited q

data with high proportion of nondetects has not been established. Tdifference that can be detected reliably by the statistical tests was not 

This deficiency should be corrected before RPRT‐0053 is adopted as a

procedure for evaluating coworker models.

• If the quantity of data is insufficient to provide adequate power of res

the test, differences may go undetected. Accepting the null hypothescould often be very claimant unfavorable.

• The Data Quality Objectives (DQO) process should be used to define t

Region for the test, and to balance Type 1 and Type 2 decision errors. MARSSIM procedure for conducting hypothesis tests is depicted in Fig

• In our review, we examined SRS Logbook Np OPOS data for 1961–198

The WRS test shows slightly less power than the t‐test for these datas

found there are sufficient data in 1961–1963 to detect differences as 

factor of 2. The year 1985 produced anomalous results in this analysi

years, the WRS test cannot reliably detect differences smaller than a 

to 10 in the CTW/NCW ratio of GMs.

• Larger differences have a 95% or better chance of detection. Smaller 

cannot be detected reliably with the available data.
Figure 2. The DQO Process is Used to Define the Gray Region fo

Power is Low and Type 2 Error Rates are High Below the Upper 

the Gray Region (UBGR)
Table 2. Sample Sizes and Upper Bound of the Gray Region (UBGR) f

of “No Difference” Hypothesis with SRS Logbook Np OPOS Data 196

Number of Samples Upper Bound of Gray Region (UBGR)

Year NCW CTW t‐Test WRS Test

1961 252 57 1.5 1.5

1962 734 175 1.5 1.5

1963 362 82 2.0 2.1

1974 58 10 3.5 3.8

1975 64 21 3.4 3.8

1977 43 11 8.4 10.2

1978 73 19 3.9 4.6

1979 55 12 4.9 4.6

1980 87 19 3.8 4.3

1981 99 23 4.4 4.5

1983 82 24 3.2 3.4

1984 92 25 3.8 4.1

1985 62 13 29.0 57.4

1986 65 13 5.5 5.6

1987 81 15 6.4 8.6

1988 77 13 5.0 5.0

1989 69 17 7.9 11.0
C. LEVEL OF CONFIDENCE (Finding 5

• The test procedures recommended in RPRT‐0053 r

high level of confidence before deciding that two w

groups are significantly different.

• This is not claimant favorable, since there is a trad

between high confidence and power to detect diffgiven a fixed sample size. A high level of confidenc

reduces the power of the test to detect difference

• Conducting the 2‐sided test of the “No Difference”

hypothesis at a 90% level of confidence would resu

lower Type 2 error rates and be more claimant fav
D. 1‐SIDED VERSUS 2‐SIDED TESTS (Recommend

• RPRT‐0053 recommends using 2‐sided tests to determine 

a significant difference between groups of workers. The n

hypothesis for these tests states there is “No Difference” 

the two groups. This form of test is not claimant favorab

as it places the burden of proof on the CTW claimants to 

that a significant difference exists.

• In the specific case of the SRS SEC for CTWs, a 1‐sided tes

appropriate, as it addresses directly the question at hand

CTW samples higher than the NCWs, or not? There are t

possible forms of null hypothesis for a 1‐sided test:

(1) H0: FNCW > FCTW

or

(2) H0: FNCW < FCTW
D. 1‐SIDED VS. 2‐SIDED TESTS (Recommendation 1 ‐ con

• With either selection, the null hypothesis may not be rejected simply because the

insufficient data. In English, the two options are as follows.

(1) Assume that NCW exceed CTW, and look for evidence in the data that this as

false (i.e., CTW are lower, until proven higher)

This option is not claimant favorable in the SRS applications, as it places the bur

the CTW claimants to provide sufficient data to prove their exposures were high(2) Assume that CTW exceed NCW, and look for evidence in the data that this asfalse (CTW are higher, until proven lower)It is more claimant favorable to choose the second form of null hypothesis for a 

it places the burden of proof on NIOSH to provide evidence that the NCW distrib

the CTW distribution. Groups of workers with suspected high exposures shouldifferent in the absence of strong evidence that they are not.

• NIOSH might consider using the second form of the 1‐sided hypothesis test instead 

test now used. The non‐parametric Peto‐Prentice test is more generally applicable tparametric MCPT, and may be applied using the more claimant‐favorable 1‐sided nu

number (2) above. This is more likely to result in a claimant‐favorable coworker mo
REFERENCES

ORAUT‐RPRT‐0055: A Comparison of Exotic Trivalent Radionuclide 

Models at the Savannah River Site, July 2012

ORAUT‐RPRT‐0056: A Comparison of Neptunium Coworker Models Savannah River Site, August 2012.

ORAUT‐RPRT‐0058: A Comparison of Mixed Fission and Activation Coworker Models at the Savannah River Site, September 2012.SC&A 2010a. Review of ORAUT‐0075: Use of Claimant Datasets fo

Modeling for Construction Workers at Savannah River Site, S. Cohe

Associates, January 2010.SC&A 2010b. Comparison of Claimant Tritium Samples from Constr

Trade Workers and Non‐Construction Workers at Savannah River Si

Cohen & Associates, November 2010.