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A similar pattern was observed for coronary artery disease (CAD -related mortality; inCAD -relatedstmortalityarincreasedadjustment relatiofship between self-rated health and mortality.
One item was integrated to detect whether or not an adjustment of variables was performed.
However, the sample size was large enough to provide a strong adjustment of variables in the models.
Forward stepwise regression modelling allowed for adjustment of variables significant at the bivariate level (see Table 3).
Adjustment of variables revealed a quantitative shift in percent differences within each of the geocoding methods but the qualitative comparison between methods remained similar.
Adjustment of variables was carried out using a univariate general linear model; the variable to be adjusted was the dependent variable and the group (control, SMI, or absence of SMI) the independent variables.
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Also, the update of national guidelines did result in adjustments of variables included and subsequent adjustments were made to the denominators in the analysis.
Finally, we use impulse response function and variance decomposition base on VEC model to find out the effects and contribution of shocks on the adjustment path of variables.
Adjustments of variable parameters during the both knitting and composite manufacturing process, were being precisely concerned in order to provide highly-qualified and mechanically-improved composite panels.
After the adjustment of the variables of block 1 all of the variables remained associated.
Second, despite our adjustment of those variables available, we recognize that we may have omitted additional variables of prognostic importance.
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