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Goldberger takes this to mean "How does the average value of one variable vary with one or more others?" and so takes the population conditional mean function as the target of empirical research.
It not only takes into account the community-embedded nature of respondents in the data, but also allows testing whether the relationships between predictor variables and the outcome variable vary across communities or are contingent on community characteristics.
The underlying Stata model for the t-test was < by varx, sort: ttest vary, by (varx2)>, whereby varx = day variable, vary = OD value, varx2 = independent variable, for the general linear model it was < xtmixed vary varx2.
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The pattern and the number of SNPs with correlation to each environmental variable varied (fig. 5a f).
The percentage of missing values per variable varied from 0.1% (physical activity) to 17% (dietary intake).
The range of values of this aggregate score variable varied from 0 to 4 points.
The percentage of missing values per variable varied from 0.2%% (physical activity) to 2.6 % (TNF-α).
If the explanatory variable varied over the three years, and the outcome variable also varied but with a different pattern, then no association could be found and this was interpreted as a lack of short-term effect.
A series of experiments was designed based on a central composite design (CCD) for three independent variables, and each variable varied at three levels.
Each risk present resulted in one point, hence the range of possible scores individuals could attain on this variable varied from zero to seven.
Variables vary.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com