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Utilizing an LSS on the subspaces of a PSS provides a sampling strategy that reduces variance associated with both main effects and variable interactions and can be designed specially to minimize variance for a given problem.
When both main effects and first-order interactions are looked for, experimental designs usually require a high number of experiments as soon as one of the investigated factors has more than two levels of variation.
Results showed that the final model consisted of both main effects and interaction terms between risk factor categories and had an adjusted R2 value of 0.85, a significant improvement over models developed for the individual categories.
The chemical data was evaluated using analysis of variance (ANOVA) and survival analysis techniques to determine both main effects and important interactions for all the experimental variables during the 203-day study.
In this paper, we theoretically show that FAST analysis can be used to estimate partial variances contributed by both main effects and interaction effects of model parameters using different sampling approaches (i.e., traditional search-curve based sampling, simple random sampling and random balance design sampling).
Random-effects models were used for both main effects and a sensitivity analysis.
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The statistical analysis of experimental results showed that both main effect and interaction effect of factors investigated were effective on the wear behavior of Al SiCp composites.
Both main effect and interaction terms were included in the analysis.
For the genetic SNP models, analyses were conducted on both main effect and epistatic models for FTO SNPs alone, adiponectin pathway SNPs alone, and the combination of both at each time point.
For both main effect and network analysis, to determine whether groups of metabolites that shared common responses were enriched for particular metabolic pathways, we used the program Mummichog (Li et al., 2013).
For the two sets of comparisons, both main effects (group and day) and interaction (group versus day) were obtained as statistical parametric maps.
More suggestions(15)
both convective effects and
both curvature effects and
both main factors and
both main trends and
both unilateral effects and
both single effects and
both microstructural effects and
both visual effects and
both stochastic effects and
both direct effects and
both demographic effects and
both strategic effects and
both spatial effects and
both maternal effects and
both electrostatic effects and
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