Review of the Hanford Thyroid Disease Study Draft Final Report (2000) / Chapter Skim
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6 Statistical Power and Interpretation of the Study
6 Statistical Power and Interpretation of the Study
Pages 99-110
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From page 99... ...
FACTORS IN STATISTICAL POWER Because the study results were essentially negative (that is, a finding of no increase in thyroid disease among those with higher estimated levels of AT exposure compared with those with lower estimated levels) , a critical issue is how to interpret the negative findings correctly.
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From page 100... ...
Similarly, a negative finding that is due to limitations in the assessment of thyroid-disease rates, because of either poor data collection or small numbers of subjects, does not support a conclusion that downwinders' disease patterns are unrelated to Hanford exposure patterns. The power of a study of this type to detect a hypothesized increase in disease prevalence per unit dose (an absolute risk of 2.5% per Gy was used in the power calculations for thyroid carcinoma)
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From page 101... ...
Distributional assumptions must be made in computing the power of the statistical tests or sample size for a specified power, and one can ask how robust the results were to these assumptions. The HEDR project acknowledged that parameter values used in its dose-reconstruction process were uncertain.
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From page 102... ...
instead, in the power calculations, the distribution of the median dose estimate for each person is used as though it is equivalent to true dose. it would be valid to ignore the dosimetry errors in the calculation of the statistical power for detecting nonzero parameter values in a linear dose-response mode!
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From page 103... ...
For example, if all the errors in the doses were due to uncertainties in the milk transfer coefficient appropriate for herds near Hanford, this would affect all doses multiplicatively; the estimated slope terms would retain the uncertainty, even in an infinitely large epidemiologic study. VIOLATION OF THE BERKSON ERROR ASSUMPTION If the first criterion is met, the statistical literature indicates, the estimation of linear dose-response models is essentially unaffected by independent dosimetry errors.
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From page 104... ...
As described in section Lit of the Draft Final Report, the noncentrality parameter governing the power of the study is equal to NCP = I /2NB2cr2t ~ + .
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From page 105... ...
The mean estimated dose in the HTDS Draft Final Report is IS2 mGy with a variance equal to (227 mGy)
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From page 106... ...
(2) in this model, it is the estimated doses that are randomly distributed, multiplicatively, around the true doses.
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From page 107... ...
A worst-case scenario, in which all the error seen in figure vIrI.4 of the Draft Final Report is due to independent errors in equation 2, would produce very low power to detect a positive dose-response relationship. For a number of reasons, however, it is considered unlikely that such a worse case actually applies.
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From page 108... ...
The HTDS Draft Final Report did investigate the effect of substituting defaults for estimated milk consumption (reference values, rather than each subject's individual estimate) in the HEDR model for thyroid dose estimation.
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From page 109... ...
and sensitivity (of the primary analysis) to error in the individual diet estimates should be discussed in future revisions of the Draft Final Report.
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From page 110... ...
it is possible that important known or unknown covariates for thyroid-disease risk, not considered in the study, could lead to biases or loss of power if they tend to cluster by geostratum, distance from the Hanford facility, or otherwise in ways that affect estimated doses. To take an unlikely example, adult weight has been found in case-control studies (McTiernan and others, 1987; Preston-Martin and others, 1993)
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