Intercorrelation, effect

Because of the way the data was created, we can rely on the calibration statistics as an indicator of performance. There is no need to use a validation set of data here. Validation sets are required mainly to assess the effects of noise and intercorrelation. Our simulated data contains no noise. Furthermore, since we are using only one wavelength or one factor, intercorrelation effects are not operative, and can be ignored. Therefore the final test lies in the values obtained from the sets of calibration results, which are presented in Table 27-1. 

The VIF for each X is shown to help assess the intercorrelation effects. 

Fig. 42 EA 3580 Intercorrelations among 12 performance tasks after intramuscular ID50 (shown by squares of varying density) increase and decrease as drug effects wax and wane.

To demonstrate this statistically, Phil Kysor and I compiled the intercorrelations among the 12 tasks at various experimental times (Fig. 42). Statistically, the matrices shown above simply demonstrate that the variance in scores are progressively accounted for by intensity of dmg effects. Thus, one can predict individual impairment in all skill areas by the degree to which drug action affects performance in any single task. This applies, incidentally, to individuals who may be quite dissimilar in various abilities prior to the administration of a belladonnoid drug such as EA 3580. 

Although the MCR method can be a very effective exploratory method, several warnings are appropriate. One must be careful interpreting MCR-determined K and C as absolute pure component spectra and pure component time profiles, respectively, due to the possible presence of intercorrelations between chemical components and spectral features, as well as nonlinear spectral interaction effects. Furthermore, the optimal number of components to be determined (A) must be specified by the user, and is usually not readily apparent a priori. In practice, A is determined by trial and error, and any attempts to overfit an MCR model will often result in K or C profiles that either contain anomalous artifacts, or are not physically meaningful. The application of inaccurate or inappropriate constraints can also lead to misleading or anomalous results with limited or no information content. 

It is, of course, very difficult to separate the effects of geothermal gradient from overburden pressure. In a given region the two are intercorrelated. 

Our basic assumption of the intercorrelation of the migration coefficients and surface absorption coefficients to the migration through fissures is verified. However, a great deal of effort must be spent studying the effects of other solute species, the chemical nature of the plutonium itself, and the kinetics of the absorption process before any understanding of the macroscopic characteristics of the transport of plutonium can be reached. 

Miller If the optimal phenotype— that is the unmutated genome, the species-typical genome—represents high g, then as you accumulate more and more deleterious mutations that each have pleiotropic effects in multiple systems, they re going to introduce the correlations between deficits in multiple systems. This will in turn introduce higher intercorrelations at lowerg levels. 

J. Maier, Mass transport in the presence of internal defect reactions-concept of conservative ensembles I, Chemical diffusion in pure compounds. /. Am. Ceram. Soc., 76(5) (1993) 1212-1217 II, Evaluation of electrochemical transport measurements, ibid., 1218-1222 III, Trapping effect of dopants on chemical diffusion, ibid., 1223-1227 IV, Tracer diffusion and intercorrelation with chemical diffusion and ion conductivity, ibid., 1228-1232. 

Are intercorrelations substantial If so, are they reasonable and understood What effects may they have on interpretation and decisions with respect to specific goals ... 

These two sets of scales agree in their general trend, but are often at variance when values for any two particular solvents are taken. Some intercorrelations have been presented by Taft et al., e.g., the parameters E, AN and Z can be written as linear functions of both a and 7t. Originally, the values of E,- and Ji were conceived as microscopic polarity scales reflecting the local polarity of the solvent in the neighborhood of solutes ( effective dielectric constant in contrast to the macroscopic one). In the framework of the donor-acceptor concept, however, they obtained an alternative meaning, based on the interrelationships found between various scales. Along these lines, flie common solvents may be separated into six classes as follows. 

The amount of information obtainable from any QSAR analysis, and hence ultimately its predictive power, largely depends on the initial design of the underlying experimental study. Only if the compounds included in the test data set are true representatives of the chemical class(es) concerned, can the maximum information be extracted from the data. The members of the training set, which are used to derive the model, should be as diverse as possible with respect to their structural features. In statistical terms this means that they should reveal minimum intercorrelation and maximum variance in the properties regarded relevant for the effects studied. 

Intercorrelation (or multicollinearity) phenomena also reduce the effectiveness of a calibration. First, there can be intercorrelation between the constituents in the samples. For example, water and fat in some meats are negatively correlated and it is possible to obtain the same calibration wavelengths for both components although the two components do not absorb in the same band. 

Practically, the ageing, tear, and fatigue processes concomitantly occur and are strongly intercorrelated each to other. The medium nature also plays an important role on these processes. In the case of polymer fracture, the medium effect may be concretised in... 

A remark applies to the experimental values of deduced from experimental bandshapes. Since we deal with total (multimolecular) correlation functions, their moments might also contain contributions arising from the intercorrelations of different molecules - or multimolecular effects - since cross terms in the statistical averages do not necessarily vanish. On this account it is necessary to estimate the extent of high-frequency collective effects if any, whenever torques are to be computed from the spectral moments. 

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