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Here, a methodology for improved multivariate modelling in supersaturation control with reduced calibration effort is developed.
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However, before we start with the individual models we observe that the univariate and multivariate models in Table 2 shows similar overall pictures.
The patterns of co-occurrence among the physical, mental and behavioral health problems were generally maintained in the multivariate models in Table 3.
We built a multivariate model in using few stations (3 stations) separated with irregular distances from 26 km to 56 km.
The multivariate model in Table 3 for never-married women shows that the odds of never-married women justifying wife-beating were lower in 2008 and 2013 relative to 2003.
The multivariate models in Table 3 show the odds ratios estimating the likelihood that female respondents would accept that husbands are justified in hitting or beating their spouse under at least one circumstance.
Variables that were not significantly associated with the outcome (α>0.05) were removed from the full multivariate model in succession.
We added variables that were found to be associated with interruption in care or death in univariate analysis (p-value <0.25), to the multivariate model, in order to evaluate multiple factors simultaneously.
In order to ascertain the interrelationships between HMW adiponectin, leptin and inflammatory cytokines/chemokines, individually or in combinations, with sex, adiposity or IR, we performed correlation analyses and constructed multivariate models in the combined study population and within each sex.
Considering a multivariate model in the meta-regression results, case definition was not a significant source of bias in the meta-analysis, while the different mean age of cases and violation of HWE were significant sources of heterogeneity.
We validated our multivariate model in our population (internal validation) [ 39].
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