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For both parameters, the largest differences were achieved for a high temporal correlation coefficient very close to one where expected accuracies rapidly degrade.
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For both approaches, for all distributions and for both parameters, the smaller is p, the larger are the bias and the mean squared error (Tables 2, 3 and 4).
Among the ROTEM parameters, the largest AUCs were found for the clot amplitude (CA) 5 value in both the EXTEM and FIBTEM assays.
However, the more covariance parameters, the larger the chance of non-convergence problems.
Clearly, the smaller the set of unidentifiable parameters, the larger the set of identifiable parameters or, equivalently, the larger the number of parameters for which the least squares parameter estimation problem can be solved.
This allowed us to identify the parameters with the largest influence on trial outcome.
The larger the absolute value of the phase modulation parameter, the larger the shifting.
As can clearly be seen, both parameters have large overlaps in their distributions of detected and undetected partial errors.
The parameter with the largest marginal effect on both accuracy and retention was g s, the maximum proportion of gaps allowed in a sequence.
Importantly, the α parameter conferred the largest improvement to model fit in yeast for any parameter (table 2 LRT(3)).
The parameter with the largest value of (21) is selected.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com