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Of course, the difficulty for non-experts in any given field is to be able to recognize when particular annotations really are errors, and failure to identify them as such leads to the danger of error propagation.
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The empirical evidence regarding the danger of systematic error suggests that inclusion of bias-controlling measures; such as randomization, blinding and attrition control, into the study design of clinical trials is justified.
Due to the poor quality of the primary research, and the danger of beta errors in this body of work, uncertainty about the value of routine physiotherapy in the prevention of pulmonary complications following abdominal surgery, remain.
The dangers of systematic error regarding the internal validity of acquired knowledge are highlighted on the basis of empirical evidence.
To keep the danger of a type I error small, the empirical significance level is computed in an actual statistical test procedure, and only if this probability is small (smaller than or equal to a pre-specified α), it is concluded that the test concentration had a systematically higher effect than the control condition.
One could, without danger of error, denounce the picture as the ultimate waste product of a corrupt and exhausted system.
The danger of overemphasis of past errors is that the drive for control may be weakened.
The dangers – of bio-error or bio-terror – may be great, but not in principle greater than those posed by natural organisms put to evil or casual use.
We believed the dangers of compounded errors would make the SPEDRE method less robust to noisy data than simulation-based methods.
On the other hand, analytical clinical judgment that is not informed by high internal validity synthesis becomes in time obsolete for patient treatment and faces the danger of being affected by systematic error.
As such it always runs the danger of committing either type I errors which occur when someone who deserves the benefits is denied (underpayment, false positives), or type II errors, which occur when benefits are paid to someone who does not deserve them (overpayment, leakage).
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com