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The data were statistically analyzed using the following settings: error model ´max (average, actual)', 0.01 proportion of highest variance values to be removed before variance averaging, 10 degrees of freedom for the Bayesian error model, 0.05 Benjamini and Hochberg False discovery rate (FDR) threshold, zero mutations.
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Whatever the calculation formulas that are used, tidal volume settings errors are limited, whereas height estimates are usually higher than exact height.
In some settings errors in dietary recall could be worse than the repeat reliability of a biomarker, in which case our methods might harm rather than improve the accuracy of exposure assignment compared to using a single biomarker alone.
11.6% (21 of 181) and 11.1% (7 of 63) of the statistical results published in Nature and BMJ respectively during 2001 were incongruent, probably mostly due to rounding, transcription, or type-setting errors.
Model (1) can be modified to accommodate settings with error-prone covariates as well.
It is possible to extend our method to more general settings where error-prone binary covariates may be more than two, or/and replicates of surrogate measurements can be arbitrary, or/and error-free covariates are also present.
The HKSJ procedure ensures the coverage probability only when the included studies' standard errors s i are similar; for unbalanced settings, the actual error probability tends to exceed the targeted one.
Previous studies of prescriptions in hospital settings have suggested error rates of about 5 per 100 paper prescriptions.
Some results on independent random error settings are extended.
Finally, we give a Monte Carlo approximation algorithm for computing the probability of a candidate winning in any settings, with an error that is as small as desired.
The ML method estimates the parameters in a prediction error settings, i.e. the sum of squared prediction error is minimized.
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