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Both of these errors rested on the demand for the 'forcible assimilation' of all propositions to a single type.
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Both of these introduce errors in the mean envelop.
Both of these measurement errors may bias the effect estimate toward null, whereas uncontrolled confounding factors in panel studies and cross-sectional studies most likely increased the estimated effect size.
The deeper causes of these errors vary.
Neither of these errors occurs here.
Due to both of these types of errors, probe spots consist of a heterogeneous mixture of probes.
Over the 3-month observation period, 52% of residents were exposed to one or both of these more serious errors.
Both of these sources of error, combined with different levels of systematic error in rate estimation on branches of different lengths, likely led to erroneous estimates of rate variation in datasets of variable branch lengths (Figure 4).
We apply analytic methods to address both of these potential sources of error using frequentist and Bayesian methods to account for exposure measurement error and we perform several sensitivity analyses [ 21, 22].
Although both of these causes of measurement error may introduce bias into the results of the study, the likely direction is toward the null hypothesis that RDTs had no effect on the use of antimalarial drugs.
A less optimal situation was that the markers were only in partial linkage disequilibrium (LD) with the polygenes (IL), or even worse, the markers were completely unlinked to the polygenes (UL); in both of these cases, type I error rates were inflated.
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