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The statistical significance of linear, quadratic and interactive terms of these factors were examined and second order polynomial models were successfully fitted to the experiment data.
where Y is the predicted response for soil release rating or for K/S value, β0 is an intercept, βi, βii and βij are the coefficient of the linear, quadratic, and interactive terms of regression equation; and χi, χii, and χij represent the coded independent variables, respectively.
The significance of the linear, quadratic, and interactive terms of the model was verified in the same manner.
The interactive terms of health literacy and better perceived understanding of health education and instructions showed no significant difference (coefficient: -0.95 and -0.66 for better understanding of health education and instructions versus marginal and adequate level of health literacy, respectively).
When we controlled for confounders, neither the main effects of self-reported stress and bone lead (tibia lead or patella lead) nor the interactive terms of self-reported stress by bone lead were significant predictors of baseline hypertension status (Table 2).
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To test the proportionality assumption of the models, we included in the model the interactive terms for exposure variables of interest with survival time.
Linear regression analyses on mean score revealed that the best fit of the data was provided by a model including an interactive term for number of trials and group (adjusted R = 0.86).
Interactive terms coefficients of X12, X15, X24, and X45 were significant.
Variance of the linear term, quadratic term and interactive term for design parameters in the response variables were analyzed.
For the fraction of cells disrupted response (Eq. 8), all the linear and quadratic terms were significant (Table 4), but two of the interactive terms (i.e. AB and AC) were not significant.
Moreover, many of the interactive terms involving prices and assets are significant, suggesting that the returns to assets are quite dependent on prices.
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