The most important variance-reducing techniques are stratified sampling, importance sampling, globally adaptive subdivision, and quasi-random sequences.
In the present study, we used a new method to illustrate to what extent the GxE of n-3 PUFA contributed to the variations of T2D-related traits and to characterize the most important GxE variance contributor among these fatty acids at the genome level.
The second most important variable was precipitation of the driest month, explaining 13.6±8.7% of the variance.
Factoring all the above in we now have the following: And The assumption made by many evolutionary biologists is that \(V_I, V_{G\times E}\) and \ \COV(G,E \) are generally small and the most important component of variance from an evolutionary standpoint is \(V_A\).
Fourth, and perhaps most important, decomposing Y variance in this way appears to be intuitively clear.
For improved function at discharge, reduction of catastrophizing was the most important predictor (explained variance 19.4%).
The 2nd most important source of variance, represented on the vertical axis, corresponds to "independence from glasses".
This solution revealed a different model in terms of factor positioning, with factor 2 (F2) being the most important in explaining variance.
The 2nd most important source of variance resulting from the PCA and corresponding to "independence from glasses", allowed differentiation between mono-focal and ReSTOR® patients after the 2nd eye surgery.
However, our morphometric [ 44] analysis reveals for the first time the shapes representing the most important degrees of variance in growth cone morphology (i.e., eigenshapes), how the projections of these shapes vary through time (i.e., oscillations), and how they are correlated with growth cone movement (i.e., growth cones with strong fast shape oscillations tended to extend faster).
