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Although the full model without the Distance to TSS variable is a substantial improvement on the empty model, the pseudo-r suggests much variance remains unexplained.
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However, much of the variance remains unexplained, suggesting that the two measures of conservation effort are complementary.
The regression models suggest that there are factors associated with change in BMI, but much of the variance remains unexplained, and the models must be interpreted with caution due to the wide confidence intervals associated with many of the estimates.
LMM enable the researcher to examine both differences in subject-level predictor variables (e.g., extent and chronicity of SLEs) and random between-subject variance in trajectories (HRQoL) in a given longitudinal data set and to assess how much variance between subjects remains after including fixed effects in a model [ 68].
This permits estimation of a general construct over very different observational contexts and respondent groups, since the much of the conditional variance remains essentially unaddressed or inferred [ 19].
Recent advances in genome-wide association studies have identified many polymorphisms that are linked to obesity, yet much of the genetic variance remains unexplained.
However, given that reported heritability estimates for BMI are typically much higher 40-700% [ 6]), a substantial proportion of the variance remains unaccounted for.
A major part of the variance remains unexplained.
Despite this, much remains uncertain: How much medication is too much?
Much bitterness remains.
Much work remains.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com