For this same reason, there should be less variance from year-to-year for a given month in a given location.
The overall model was significant (F4,455 = 65.8, p < 0.001) and explained slightly less variance than for the AIOS-24h ratings (RADJ = 22%).
Less variance was accounted for in the ADHD group than in the comparison group.
Indeed, sensitivity accounted for less variance than was expected (effect sizes 0.24-0.32).
There was a less variance in risk ratios for recurrent events across disease subtypes.
As more variance in a measure is accounted for by the progressively interfering factor, less variance is left to be accounted for by the true NK or IFN activity factor.
Thus, as can be seen in Table 1, the reduced model which did not include bias (but which did include the other four predictors) accounted for significantly less variance in participants' responses than the full model.
Only one PSF was identified in methylation ranked as the 22nd IC, accounting for much less variance (0.2% of total methylation variance) compared to the PSFs identified in the SNPs, which implies that population structure does affect methylation but is not the largest influencing factor.
When all the items were combined there was less evidence of unidimensionality with the first factor explaining less variance than the subscales and for hip OA two factors were identified from the MAP analysis.
