Regression effect

Factors Given effects Estimated effects Multiple regression effect estimate... 

The predictive equations used in this work presented small errors over the age range. FFM, %FM and TBW, based on measured R and Xc, were consistent with the ones reported in the literature [11,15]. In addition, other works have indicated that the phase angle is important for evaluating health status [7,16]. It is important to emphasize that PA value depends only on the R and Xc measurements and it is free from the statistical regression effects contained in the predictive equations. Barbosa-Silva et al (2005) determined PA values from 6.5 to 9.0 degrees of healthy adults aging from 40 to 49 years old. These findings are compatible with the results of this work. Caution has to be taken due to the faet that bioimpedanee is a limited technique for body composition due to population differenees. Even so, it is still eonsidered an important tool for health professionals [8]. 

Figure 4.5 shows the values of the three components of the adjusted data, provided with Model 5. Figure 4.5 shows a method to approximate the observed data (the log number of fatalities) with the sum level + regression effects + interventions effects, after the seasonal and the residual are subtracted from the adjusted data. 

On the other hand, techniques like Principle Component Analysis (PCA) or Partial Least Squares Regression (PLS) (see Section 9.4.6) are used for transforming the descriptor set into smaller sets with higher information density. The disadvantage of such methods is that the transformed descriptors may not be directly related to single physical effects or structural features, and the derived models are thus less interpretable. 

Using a multiple linear regression computer program, a set of substituent parameters was calculated for a number of the most commonly occurring groups. The calculated substituent effects allow a prediction of the chemical shifts of the exterior and central carbon atoms of the allene with standard deviations of l.Sand 2.3 ppm, respectively Although most compounds were measured as neat liquids, for a number of compounds duplicatel measurements were obtained in various solvents. 

The value of d obtained by linear regression is 0.96 with a correlation coefficient of 0.9985. For 2 alkylpyridines 8 is 2.030 (256), which leads to the conclusion that 2-alkylpyridines are twice as sensitive to steric effects as their thiazole analogs. 

Probucol. Probucol is an antioxidant that is effective in lowering LDL cholesterol. Whereas probucol was known to lower cholesterol after relatively simple clinical trials (160), its mechanism of action as an antioxidant in the treatment of atherosclerosis is quite novel. Probucol has been shown to have the abiUty to produce regression of atherosclerotic lesions in animal models (161). Probucol therefore represents a novel class of pharmaceutical agent for the treatment of atherosclerosis. This effect occurs mechanistically, in part, by preventing oxidation of LDL, a necessary step in foam cell formation. This antioxidant activity has been shown in laboratory experiments and its activity in lowering LDL cholesterol in human studies is well documented (162). 

Methyldopa is effective in mild, moderate, and severe hypertension but a thiazide-type diuretic is needed to overcome the fluid retaining side effect. Methyldopa has been shown to prevent and induce regression of ventricular hypertrophy in hypertensive patients. The principal side effects are sedation, drowsiness, nasal congestion, fluid retention, and in rare occasions, hemolytic anemia. 

The manual evaluation and the multiple regression results are in good agreement. The result from the log rates is still very close The evaluation by multiple regression is shown in Appendix E. The reader is encouraged to do the manual evaluation of effects of C and M ( m and n exponents) and compare those with the multiple regression results. 

It may be necessary and possible to achieve a good Brf nsted relationship by adding another term to the equation, as Toney and Kirsch did in correlating the effects of various amines on the catalytic activity of a mutant enzyme. A simple Brf nsted plot failed, but a multiple linear regression on the variables pKa and molecular volume (of the amines) was successful. 

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