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Setting the sample two years in the past as opposed to one or three years is admittedly arbitrary.
Setting: The sample of 503 subjects was recruited at two local outpatient clinics in Hong Kong.
The Cramér-Rao bound was chosen as a tool for setting the sample size for the three basic types of the state estimation, for filtering, prediction and smoothing.
Meanwhile, the sample size estimation and rationale for setting the sample size in "study design", which was designed based on 3-month lag censoring analysis, was not amended.
There is the additional issue that setting the sample size too high may lead to a preventable failure to reach the recruitment target [ 12].
The rationale for setting the sample size at 250 subjects per group is based on "data handling procedure #2: 3-month lag censoring analysis" as follows.
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In our current implementation, we set the sample size to 10%, for performance and scalability reasons.
On Easy-nLC 1000 UHPLC, set the sample loading and RP gradient method as follows.
We set the sample size N = 1000, and the simulation results are achieved by 20,000 Monte Carlo simulations.
Given the above, we set the sample size according to the Provisions for Drug Registration.
We set the sample size as the number of site patterns in the alignment.
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