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GMs are probabilistic models where an edge between two variables illustrates their conditional dependence given all other variables in the model.
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This chapter presents methods for estimating the aforementioned variables, illustrated with solution of real problems.
Mediating variables illustrate the transmission mechanism between independent and dependent variable, such as EO and performance.
SNPs of interest were investigated for possible associations with other clinical variables illustrated in Table 1.
Binary logistic regression model for caries, adjusting for all variables illustrated above.
All means and standard deviations for continuous variables and frequencies for categorical variables illustrated in the tables are weighted.
We present a methodology to obtain dichotomised outcomes for skewed variables illustrated with data from several observational studies.
The assumption of casual ordering of variables, illustrated above, is based on the review of the literature presented above.
A comparison of the two response variables illustrated the discordance in the form of lower disease control by FDG-PET/CT relative to CT.
However, 3 month follow up is too early to evaluate numerous outcome variables, illustrated by low SMR for several of the instruments tested.
This plot, analogous to the plot shown in Figure 2 for the 15 toxicity variables, shows the clustering of toxicity and chemical component variables, illustrating the chemical components that were most closely associated (covaried) with lung toxicity.
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CEO of Professional Science Editing for Scientists @ prosciediting.com