Behavioral research independent variables

To overcome this weakness, we are developing a quantitative structure-activity strategy that is conceptually applicable to all chemicals. To be applicable, at least three criteria are necessary. First, we must be able to calculate the descriptors or Independent variables directly from the chemical structure and, presumably, at a reasonable cost. Second, the ability to calculate the variables should be possible for any chemical. Finally, and most importantly, the variables must be related to a parameter of Interest so that the variables can be used to predict or classify the activity or behavior of the chemical (j ) One important area of research is the development of new variables or descriptors that quantitatively describe the structure of a chemical. The development of these indices has progressed into the mathematical areas of graph theory and topology and a large number of potentially valuable molecular descriptors have been described (7-9). Our objective is not concerned with the development of new descriptors, but alternatively to explore the potential applications of a group of descriptors known as molecular connectivity indices (10). 

For example, suppose a researcher wanted to test the effect of vitamin A on the ability of rats to see in dim light. The independent variable would be the dose of Vitamin A added to the rats diet. The dependent variable would be the intensity of light that causes the rats to react. All other factors, such as time, temperature, age, water given to the rats, the other nutrients given to the rats, and similar factors, are held constant. Chemists sometimes do short experiments just to see what happens or to see what products a certain reaction produces. Often, these are not formal experiments. Rather they are ways of making additional observations about the behavior of matter. 

On the road studies fall into two general types those that involve some manipulation of the situation, and thus an independent variable is actually manipulated and those that simply observe behavior of unsuspecting drivers under various naturally occurring situations, d thus all variables - independent and dependent - are not under direct control of the researcher. 

We emphasize at this point that all these pretransitional chain stretching effects found in the simulations are at variance with the simple RPA treatment as embodied in Leibler s theory this simple form of the RPA would mean only that all the ratios shown in Fig. 7.38 should be strictly unity, irrespective of e and N. Thus the simulations reveal rather drastic deviations from RPA, a hitherto somewhat unexpected result, since for dense melts the RPA has been taken as basically exact by many researchers. In this context, it is also important to recall that these deviations from the RPA should not be attributed to the vacancy content of the model (recall that Fig. 7.17(a) has studied this behavior for variable vacancy content, and behavior independent of cj>v for T > Tc was found " ). 

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