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This way, the means of measuring your success is still in place, but you can adjust the means by which you arrive at it without breaking your own rules.
Because there is only one covariate value for a given participant, the ANCOVA model would not be able to appropriately use the covariate to adjust the means for such a voxel.
If for example, the covariate adjusted the means upward for the Average IQ participants, then this would appear to "partial out" the IQ effect for the feedback conditions, but it would also adjust the means upward and introduce spurious group differences for the response selection conditions.
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The pre-dispersion unit was a straight tube packed with nickel foam elements, used to adjust the mean droplet diameter of the dispersed phase for the HTR.
This allowed us to adjust the mean connectivity to a fixed value c = 0.05 by changing the number P of stored associations in the network.
The solution adopted was the second one, to develop a single decision tree for a QP and adjust the mean and the variance threshold used by the trees on the basis of the QP.
A value, the scaling factor, was calculated to adjust the mean of the remaining values to 100.
Second, we used the effects thus found to adjust the mean formal care costs in the four care patterns.
We used the analysis of covariance (ANCOVA) method to adjust the mean SBP values for age, ethnicity and gender.
However, if we adjust the mean high average IQ scores in the present patient group for the Flynn effect, these scores would be still in the normal range.
Leptin samples were performed in two batches, and a correction factor used to adjust the mean level in each batch to the same level prior to further analysis.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com