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Table 1 summarizes the multivariate studies that have looked at views about nanotechnology.
The review, however, also notes that this emphasis is tacitly and explicitly rejected by a range of multivariate studies that emphasize the key roles of non-awareness variables, such as, trust, general views about science, and overall worldview.
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The sample was drawn from the Twins Early Development Study TEDSS), which is a multivariate longitudinal study that recruited over 11,000 twin pairs born in England and Wales in 1994, 1995 and 1996 (Haworth et al. 2012; Oliver and Plomin 2007).
The question about chronicity was investigated by looking at prognostic studies that used multivariate analysis to identify independent predictors of persistence (chronicity).
Such a relationship often can only be adequately described and exploited by multivariate structure-activity relationship (SAR) studies that can deal with many variables simultaneously.
In most of the studies that use multivariate analyses, IMU is associated with the female sex and advanced age (Table 2).
Selection criteria Prospective cohort studies that reported multivariate adjusted relative risks and corresponding 95% confidence intervals for stroke with respect to baseline pre-diabetes were included.
Findings of studies that reported multivariate-adjusted measures of association and 95% confidence intervals (CIs), and/or standard errors (SEs) or t-values, are presented in Figures 1– 5.
In addition, subgroup analysis of studies that only used multivariate statistical analysis was also conducted (Table 2).
Quantitative genetic studies that model complex, multivariate phenotypes are important for both evolutionary prediction and artificial selection.
However, one review of ten studies that used similar multivariate analysis found that it was not possible to assess whether one specific factor was more important that the others in determining utilization [ 58].
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