Factors analyte

H. F. Gollob, A statistical model which combines features of factor analytic and analysis of variance techniques. Psychometrika, 33 (1968) 73-111. 

Multivariate chemometric techniques have subsequently broadened the arsenal of tools that can be applied in QSAR. These include, among others. Multivariate ANOVA [9], Simplex optimization (Section 26.2.2), cluster analysis (Chapter 30) and various factor analytic methods such as principal components analysis (Chapter 31), discriminant analysis (Section 33.2.2) and canonical correlation analysis (Section 35.3). An advantage of multivariate methods is that they can be applied in... 

Lochmiiller, C. H., Hsu, S.-H., and Reese, C., Prediction of the retention behavior of ionizable compounds in reversed-phase LC using factor-analytical modeling, /. Chromatogr. Sci., 34, 77, 1996. 

In Figure 5-24, the + s are the noisy original (z/ ,5,y , 10,1/ ,is)-data points. The s represent the corresponding factor analytically reproduced data points. The noise reduction is obvious, however, note that the distribution of the s along the line is still noisy. This manifests in the irregular distribution of the markers. 

V factor analytically reproduced data matrix (nsxntj... 

Equation (10.23) describes the relations of the preexponential factors to the analyte concentration in the same way as relative concentration of free and bound forms given by Eqs. (10.12) and (10.13). The preexponential factor analyte response function may be shifted toward lower or higher analyte concentrations compared to those obtained from the absorbance or/and intensity measurements (Figure 10.6) because of the apparent dissociation constant (Kd) given by Eq. (10.24). 

Trievel, R.C., Li, F.Y. and Marmorstein, R. (2000) Application of a fluorescent histone acetyltransferase assay to probe the substrate specificity of the human p300/ CBP-associated factor. Analytical Biochemistry, 287, 319-328. 

S. Tripathy, M.K. Panigrahi, N. Kundu, Geochemistry of soil around a fluoride contaminated area in Nayagarh District, Orissa, India Factor analytical appraisal. Environ. Geochem. Health 27 (2005) 205-216. 

March and Amaya-Jackson (personal communication) have developed a self-report PTSD screening measure, the Child and Adolescent Trauma Screen (CATS) that has demonstrated excellent factor analytic and psychometric properties across the domains of reexperiencing, avoidance, and hyperarousal. Amaya-Jackson et al. (2000) developed the Child PTSD Checklist, which is a child-friendly instrument with sound psychometric properties that can provide a formal diagnosis of PTSD. 

Lanz VA, Alfarra MR, Baltensperger U, Buchmann B, Hueglin C, Prevot ASH (2007) Source apportionment of sub- micron organic aerosols at an urban site by factor analytical modelling of aerosol mass spectra. Atmos Chem Phys 7 1503-1522, http //www.atmos-chem-phys.net/7/ 1503/2007/... 

Receptor models are widely used tools for apportioning concentrations of pollutants to different sources. They can be factor analytical methods (PMF, PCA, UNMIX, etc.) or chemical mass balance (CMB). On the one hand, these methods revealed to be very valuable to identify the main sources/categories of PM pollution (road traffic, secondary particles, fuel oil combustion, sea salt, etc.) but on the other hand they experienced difficulties in separating the contributions of collinear sources such as mineral dust (natural resuspension) and road dust (anthropogenic) or co-variant sources such as vehicle exhaust and road dust [34, 44, 45, 49, 55, 58, 110-113]). Significant improvements were made with the use of combination of models or constrained models such as the Multilinear Engine (ME-2). 

Tab. 7-7. Matrix of factor loadings of the common factor analytical solution of sedimented airborne dusts from Kosice (factor loadings < 0.450 are set to 0 for greater clarity)...

The features Ag and the west wind direction have very low communalities in the common factor solution, i.e. their variance does not correlate with the variance of the other determined features. Origins may be both errors in the determination of these features and the features specific variances. These features should not, therefore, be interpreted together with the factor analytical solution. The most weighted factors may be interpreted as ... 

The purpose of application of factor analysis (FA) is the characterization of complex changes of all observed features in partial systems of the environment by determination of summarized factors which are more comprehensive and causally explicable. The method extracts the essential information from a data set. The exclusive consideration of common factors in the reduced factor analytical solution seems to be particularly promising for the analytical process. The specific variances of the observed features will be separated from the reduced factor analytical results by means of the estimation of the communalities. They do not falsify the influence of the main pollution sources (see also Tab. 7-2). The mathematical fundamentals of FA are explained in detail in Section 5.4.3 (see also [MALINOWSKI, 1991 WEBER, 1986]). 

FA was used to detect the latent information within the data set. The reduced factor analytical model consists of two common factors they explain 86.6% of the data s variance. 

Famham, I.M., K.H. Johannesson, A.K. Singh, V.F. Hodge, and KJ. Stetzenbach. 2003. Factor analytical approaches for evaluating groundwater trace element chemistry data. Anal. Chim. Acta 490 123-138. 

Figler, M.H., Weinstein, A.R., Sollers, J.J. and Devan, B.D. (1992) Pleasure travel (tourist) motivation A factor analytic approach. Bulletin of the Psychonomic Society 30,113-116. 

Unlike the pre-analytical factors, analytical factors are more readily controlled within the individual laboratory. Analytical variables that are associated with the demonstration of the antigen include antibody specificity and sensitivity, dilution, detection system, and antigen retrieval. 

Secondly, a quantitative interpretation of the amide I VCD region is possible. Using factor analysis methodology, reliable percentage of a-helical, B-sheet and other contributions have been obtained, using prototypical peptide VCD spectra as basis sets. The factor analytical data appear to agree well with solid phase X-ray structures, and to a somewhat lesser extent with UV-CD data. Thus, it appears that the instrumental and computational methods are available to utilize VCD as a novel spectroscopic technique for structural studies on peptides and proteins. 

Both studies found a severe impact of food allergy on HRQL in relation to psychosocial aspects of children s and teens everyday lives. For example, in the initial focus groups put in place to generate items for the FAQLQ-PF, parents suggested that the anxiety associated with the risk of a potential reaction has more profound effects on emotional and social aspects of a child s everyday life, than clinical reactivity induced by food intake. The importance of a subscale assessing this aspect of anxiety was subsequently confirmed using clinical impact and factor analytic methodologies. 

In Chapters 2, 3, and 4, all aspects of the analyte retention on the HPLC column are discussed. There are many mathematical functions describing retention dependencies versus various parameters (organic composition, temperature, pH, etc.). Most of these dependencies rely on empirical coefficients. Analyte retention is a function of many factors analyte interactions with the stationary and mobile phases analyte structure and chemical properties struc-... 

I. Influence of capacity factor, analyte structure, flow velocity and column loading,... 

Probably the most impressive review of indicators oig is Carroll s (1993) book on the 20th century s factor analytic work (Fig. 3). This figure nicely illustrates the hierarchical aggregation developed here items —> scales —> general constructs. 

Carroll JB 1993 Human cognitive abilities a survey of the factor-analytic literature. Cambridge University Press, Cambridge... 

Although the g factor is necessarily revealed by psychometric methods, it is not exclusively a psychometric construct, nor is it a methodological artefact of the way psychometric tests are constructed or of the particular factor-analytic algorithms used to extract g. The extra-psychometric reality of g is indicated by the many significant correlations that g has with a wide variety of variables, both physical and behavioural, that have no intrinsic or conceptual relationship to psychometrics or factor analysis. In this respect, g seems to differ from other psychometric factors (Jensen 1993,1994). 

Carroll s (1993) comprehensive reanalysis of the psychometric literature led to the development of a three-stratum hierarchical model in which g occupies a singular stratum at the apex of the hierarchy accounting for approximately 50% of the covariance among diverse measures of intellect. Carroll s synthesis of the factor analytic literature is subject to two related criticisms. Horn (2000) noted that the g factor is not invariant in several different studies and thus cannot constitute a well-defined theoretical constmct. Gustafsson (1999) noted that Carroll used exploratory rather than confirmatory factor analyses. Gustafsson s confirmatory factor analyses led to the conclusion that g is identical with fluid ability (gf) and that there is no need to hypothesize an independent factor. 

Ian Deary (2000, this volume) and Arthur Jensen (2000, this volume) have rightly argued that we must distinguish between the species-typical human cognitive architecture (which may be massively modular), and the factor-analytic structure of individual differences in cognitive functioning (which yields a unitary factor). This distinction is obvious in the case of fitness itself to claim that there is an f factor in a particular species (which can capture individual differences in... 

Since the rank of Y can be estimated by factor-analytical technique with consideration of experimental noise, the number of unexpected interferents, M, can be obtained easily by subtracting N from the rank of Y. The information on the number of interferents is crucial in this situation, this makes the distinction between matrix calibration and vector calibration. Assuming the bilinear structure of the response, one can factor-decompose the overall background responses of M interferents into the product of two matrices... 

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