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An important implication of these examples for risk assessment is that the "main effects" of lead or PCBs or ETS, estimated by multiple regression, are misleading characterizations of their respective associations with neurodevelopment.
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Calculated R-squared values by single and multiple regression were 0.94 and 0.96, respectively.
The LSS for prolonged-release tacrolimus which used multiple regression was described by Niioka et al. [ 13].
The selection of the variables for the multiple regression was determined by a mathematical criteria p < 0.20 in at least one of the domains.
Note that upon further analysis, the multiple regression is affected by the high intercorrelation between age, height, weight and BMI because of their multicollinearity.
The analytic results by multiple regression models are shown in the Additional file 2. The study findings were similar by two different methods.
The associations between lipid profiles, lifestyle and other variables as assessed by multiple regression analyses are presented in Table 4.
The quadratic polynomial equations of two RSM analyses as obtained by multiple regression analysis are shown in Eqs.
Factor scores were calculated by multiple regression and were categorized into quintiles based on the total sample distribution.
All mathematical models proposed by multiple regression analysis were significant (P < 0.001) and could explain up to more than 85% of the variance (R2adj > 0.80).
Conversely, some significant associations observed by multiple regression may be due to type I error.
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