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Then, we calculate the expected squared distance from cluster members to the CH.
The expected squared distance (track segment length) is therefore E(Li2) = v2Ti2+4DTi.
Observed Minus Expected Squared is described in detail elsewhere [10], [15].
Then, the sum over a long time T of expected squared family sizes is N TF.
The second is called outfit and it is determined by the unweighted mean squared deviation from the expected response pattern.
The first is called infit and is the value of the mean squared deviation from the expected response pattern weighted by the item variance.
The LPSD is therefore the square root of the average squared deviation, conditional on a negative outcome (late arrival).
Post-hoc results might appear counterintuitive, because the test is based on a squared deviation from the expectation.
The squared deviation was smallest for the 'enhanced' treatment since it deviated least from the expected value, making the Δχ largest when comparing this treatment to the 'diminished' treatment because it had the greatest deviation from the expected value.
In this method, for each replicate, the sum of squared deviation (SSD) between the observed and expected distributions is compared with the SSD between the simulated and expected distributions using ARLEQUIN (ver. 3.5).
It's just the average squared deviation from the mean.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com