THE USE OF MULTIVARIATE ANALYSIS OF COVARIANCE IN EVALUATING THE COMPARABILITY OF LABORATORY DETERMINATIONS IN COOPERATIVE STUDIES

The role of clinical chemistry has traditionally been to evaluate acutely ill or hospitalized patients. Traditional statistical methods have serious drawbacks in that they use univariate techniques. To demonstrate alternative methodology, a multivariate analysis of covariance model was developed and applied to the data from the Cooperative Study of Sickle Cell Disease.^ The purpose of developing the model for the laboratory data from the CSSCD was to evaluate the comparability of the results from the different clinics. Several variables were incorporated into the model in order to control for possible differences among the clinics that might confound any real laboratory differences.^ Differences for LDH, alkaline phosphatase and SGOT were identified which will necessitate adjustments by clinic whenever these data are used. In addition, aberrant clinic values for LDH, creatinine and BUN were also identified.^ The use of any statistical technique including multivariate analysis without thoughtful consideration may lead to spurious conclusions that may not be corrected for some time, if ever. However, the advantages of multivariate analysis far outweigh its potential problems. If its use increases as it should, the applicability to the analysis of laboratory data in prospective patient monitoring, quality control programs, and interpretation of data from cooperative studies could well have a major impact on the health and well being of a large number of individuals. ^

Multivariate analysis of fresh-cut carambola slices stored under different temperatures.

Quality of fresh-cut carambola (Averrhoa carambola L) is related to many chemical and biochemical variables especially those involved with softening and browning, both influenced by storage temperature. To study these effects, a multivariate analysis was used to evaluate slices packaged in vacuum-sealed polyolefin bags, and stored at 2.5 degrees C, 5 degrees C and 10 degrees C, for up to 16 d. The quality of slices at each temperature was correlated with the duration of storage, O(2) and CO(2) concentration in the package, physical chemical constituents, and activity of enzymes involved in softening (PG) and browning (PPO) metabolism. Three quality groups were identified by hierarchical cluster analysis, and the classification of the components within each of these groups was obtained from a principal component analysis (PCA). The characterization of samples by PCA clearly distinguished acceptable and non-acceptable slices. According to PCA, acceptable slices presented higher ascorbic acid content, greater hue angles ((o)h) and final lightness (L-5) in the first principal component (PC1). On the other hand, non-acceptable slices presented higher total pectin content. PPO activity in the PC1. Non-acceptable slices also presented higher soluble pectin content, increased pectin solubilisation and higher CO(2) concentration in the second principal component (PC2) whereas acceptable slices showed lower total sugar content. The hierarchical cluster and PCA analyses were useful for discriminating the quality of slices stored at different temperatures.

Effect of signal intensity normalization on the multivariate analysis of spectral data in complex 'real-world' datasets

Spectral signal intensities, especially in 'real-world' applications with nonstandardized sample presentation due to uncontrolled variables/factors, commonly require additional spectral processing to normalize signal intensity in an effective way. In this study, we have demonstrated the complexity of choosing a normalization routine in the presence of multiple spectrally distinct constituents by probing a dataset of Raman spectra. Variation in absolute signal intensity (90.1% of total variance) of the Raman spectra of these complex biological samples swamps the variation in useful signals (9.4% of total variance), degrading its diagnostic and evaluative potential.

The size and shape of shells used by hermit crabs: A multivariate analysis of Clibanarius erythropus

Shell attributes Such as weight and shape affect the reproduction, growth, predator avoidance and behaviour of several hermit crab species. Although the importance of these attributes has been extensively investigated, it is still difficult to assess the relative role of size and shape. Multivariate techniques allow concise and efficient quantitative analysis of these multidimensional properties, and this paper aims to understand their role in determining patterns of hermit crab shell use. To this end, a multivariate approach based on a combination of size-unconstrained (shape) PCA and RDA ordination was used to model the biometrics of southern Mediterranean Clibanarius erythropus Populations and their shells. Patterns of shell utilization and morphological gradients demonstrate that size is more important than shape, probably due to the limited availability of empty shells in the environment. The shape (e.g. the degree of shell elongation) and weight of inhabited shells vary considerably in both female and male crabs. However, these variations are clearly accounted for by crab biometrics in males only. Oil the basis of statistical evidence and findings from past studies. it is hypothesized that larger males of adequate size and strength have access to the larger, heavier and relatively more available shells of the globose Osilinus turbinatus, which cannot be used by average-sized males or by females investing energy in egg production. This greater availability allows larger males to select more Suitable Shapes. (C) 2009 Elsevier Masson SAS. All rights reserved.

A multivariate analysis of beta diversity across organisms and environments

We examined variability in hierarchical beta diversity across ecosystems, geographical gradients, and organism groups using multivariate spatial mixed modeling analysis of two independent data sets. The larger data set comprised reported ratios of regional species richness (RSR) to local species richness (LSR) and the second data set consisted of RSR: LSR ratios derived from nested species-area relationships. There was a negative, albeit relatively weak, relationship between beta diversity and latitude. We found only relatively subtle differences in beta diversity among the realms, yet beta diversity was lower in marine systems than in terrestrial or freshwater realms. Beta diversity varied significantly among organisms' major characteristics such as body mass, trophic position, and dispersal type in the larger data set. Organisms that disperse via seeds had highest beta diversity, and passively dispersed organisms showed the lowest beta diversity. Furthermore, autotrophs had lower beta diversity than organisms higher up the food web; omnivores and carnivores had consistently higher beta diversity. This is evidence that beta diversity is simultaneously controlled by extrinsic factors related to geography and environment, and by intrinsic factors related to organism characteristics.

Optimization of River Water Quality Surveys by Multivariate Analysis of Physicochemical, Bacteriological and Ecotoxicological Data

This study aims to optimize the water quality monitoring of a polluted watercourse (Leça River, Portugal) through the principal component analysis (PCA) and cluster analysis (CA). These statistical methodologies were applied to physicochemical, bacteriological and ecotoxicological data (with the marine bacterium Vibrio fischeri and the green alga Chlorella vulgaris) obtained with the analysis of water samples monthly collected at seven monitoring sites and during five campaigns (February, May, June, August, and September 2006). The results of some variables were assigned to water quality classes according to national guidelines. Chemical and bacteriological quality data led to classify Leça River water quality as “bad” or “very bad”. PCA and CA identified monitoring sites with similar pollution pattern, giving to site 1 (located in the upstream stretch of the river) a distinct feature from all other sampling sites downstream. Ecotoxicity results corroborated this classification thus revealing differences in space and time. The present study includes not only physical, chemical and bacteriological but also ecotoxicological parameters, which broadens new perspectives in river water characterization. Moreover, the application of PCA and CA is very useful to optimize water quality monitoring networks, defining the minimum number of sites and their location. Thus, these tools can support appropriate management decisions.

Preoperative nutritional screening by the specialist instead of the nutritional risk score might prevent excess nutrition: a multivariate analysis of nutritional risk factors.

BACKGROUND: The aim of the current study was to assess whether widely used nutritional parameters are correlated with the nutritional risk score (NRS-2002) to identify postoperative morbidity and to evaluate the role of nutritionists in nutritional assessment. METHODS: A randomized trial on preoperative nutritional interventions (NCT00512213) provided the study cohort of 152 patients at nutritional risk (NRS-2002 ≥3) with a comprehensive phenotyping including diverse nutritional parameters (n=17), elaborated by nutritional specialists, and potential demographic and surgical (n=5) confounders. Risk factors for overall, severe (Dindo-Clavien 3-5) and infectious complications were identified by univariate analysis; parameters with P<0.20 were then entered in a multiple logistic regression model. RESULTS: Final analysis included 140 patients with complete datasets. Of these, 61 patients (43.6%) were overweight, and 72 patients (51.4%) experienced at least one complication of any degree of severity. Univariate analysis identified a correlation between few (≤3) active co-morbidities (OR=4.94; 95% CI: 1.47-16.56, p=0.01) and overall complications. Patients screened as being malnourished by nutritional specialists presented less overall complications compared to the not malnourished (OR=0.47; 95% CI: 0.22-0.97, p=0.043). Severe postoperative complications occurred more often in patients with low lean body mass (OR=1.06; 95% CI: 1-1.12, p=0.028). Few (≤3) active co-morbidities (OR=8.8; 95% CI: 1.12-68.99, p=0.008) were related with postoperative infections. Patients screened as being malnourished by nutritional specialists presented less infectious complications (OR=0.28; 95% CI: 0.1-0.78), p=0.014) as compared to the not malnourished. Multivariate analysis identified few co-morbidities (OR=6.33; 95% CI: 1.75-22.84, p=0.005), low weight loss (OR=1.08; 95% CI: 1.02-1.14, p=0.006) and low hemoglobin concentration (OR=2.84; 95% CI: 1.22-6.59, p=0.021) as independent risk factors for overall postoperative complications. Compliance with nutritional supplements (OR=0.37; 95% CI: 0.14-0.97, p=0.041) and supplementation of malnourished patients as assessed by nutritional specialists (OR=0.24; 95% CI: 0.08-0.69, p=0.009) were independently associated with decreased infectious complications. CONCLUSIONS: Nutritional support based upon NRS-2002 screening might result in overnutrition, with potentially deleterious clinical consequences. We emphasize the importance of detailed assessment of the nutritional status by a dedicated specialist before deciding on early nutritional intervention for patients with an initial NRS-2002 score of ≥3.

Multivariate analysis of phenol mineralisation by combined hydrodynamic cavitation and heterogeneous advanced Fenton processing

Phenolic compounds in wastewaters are difficult to treat using the conventional biological techniques such as activated sludge processes because of their bio-toxic and recalcitrant properties and the high volumes released from various chemical, pharmaceutical and other industries. In the current work, a modified heterogeneous advanced Fenton process (AFP) is presented as a novel methodology for the treatment of phenolic wastewater. The modified AFP, which is a combination of hydrodynamic cavitation generated using a liquid whistle reactor and the AFP is a promising technology for wastewaters containing high organic content. The presence of hydrodynamic cavitation in the treatment scheme intensifies the Fenton process by generation of additional free radicals. Also, the turbulence produced during the hydrodynamic cavitation process increases the mass transfer rates as well as providing better contact between the pseudo-catalyst surfaces and the reactants. A multivariate design of experiments has been used to ascertain the influence of hydrogen peroxide dosage and iron catalyst loadings on the oxidation performance of the modified AFP. High er TOC removal rates were achieved with increased concentrations of hydrogen peroxide. In contrast, the effect of catalyst loadings was less important on the TOC removal rate under conditions used in this work although there is an optimum value of this parameter. The concentration of iron species in the reaction solution was measured at 105 min and its relationship with the catalyst loadings and hydrogen peroxide level is presented.

Multivariate analysis of the Fugl-Meyer outcome measures assessing the effectiveness of GENTLE/S robot-mediated stroke therapy

Background: Robot-mediated therapies offer entirely new approaches to neurorehabilitation. In this paper we present the results obtained from trialling the GENTLE/S neurorehabilitation system assessed using the upper limb section of the Fugl-Meyer ( FM) outcome measure. Methods: We demonstrate the design of our clinical trial and its results analysed using a novel statistical approach based on a multivariate analytical model. This paper provides the rational for using multivariate models in robot-mediated clinical trials and draws conclusions from the clinical data gathered during the GENTLE/S study. Results: The FM outcome measures recorded during the baseline ( 8 sessions), robot-mediated therapy ( 9 sessions) and sling-suspension ( 9 sessions) was analysed using a multiple regression model. The results indicate positive but modest recovery trends favouring both interventions used in GENTLE/S clinical trial. The modest recovery shown occurred at a time late after stroke when changes are not clinically anticipated. Conclusion: This study has applied a new method for analysing clinical data obtained from rehabilitation robotics studies. While the data obtained during the clinical trial is of multivariate nature, having multipoint and progressive nature, the multiple regression model used showed great potential for drawing conclusions from this study. An important conclusion to draw from this paper is that this study has shown that the intervention and control phase both caused changes over a period of 9 sessions in comparison to the baseline. This might indicate that use of new challenging and motivational therapies can influence the outcome of therapies at a point when clinical changes are not expected. Further work is required to investigate the effects arising from early intervention, longer exposure and intensity of the therapies. Finally, more function-oriented robot-mediated therapies or sling-suspension therapies are needed to clarify the effects resulting from each intervention for stroke recovery.

Multivariate analysis of the dielectric response of materials modeled using networks of resistors and capacitors

We discuss the modeling of dielectric responses of electromagnetically excited networks which are composed of a mixture of capacitors and resistors. Such networks can be employed as lumped-parameter circuits to model the response of composite materials containing conductive and insulating grains. The dynamics of the excited network systems are studied using a state space model derived from a randomized incidence matrix. Time and frequency domain responses from synthetic data sets generated from state space models are analyzed for the purpose of estimating the fraction of capacitors in the network. Good results were obtained by using either the time-domain response to a pulse excitation or impedance data at selected frequencies. A chemometric framework based on a Successive Projections Algorithm (SPA) enables the construction of multiple linear regression (MLR) models which can efficiently determine the ratio of conductive to insulating components in composite material samples. The proposed method avoids restrictions commonly associated with Archie’s law, the application of percolation theory or Kohlrausch-Williams-Watts models and is applicable to experimental results generated by either time domain transient spectrometers or continuous-wave instruments. Furthermore, it is quite generic and applicable to tomography, acoustics as well as other spectroscopies such as nuclear magnetic resonance, electron paramagnetic resonance and, therefore, should be of general interest across the dielectrics community.

Multivariate analysis of the energy cycle of the South American rainy season

The South American (SA) rainy season is studied in this paper through the application of a multivariate Empirical Orthogonal Function (EOF) analysis to a SA gridded precipitation analysis and to the components of Lorenz Energy Cycle (LEC) derived from the National Centers for Environmental Prediction (NCEP) reanalysis. The EOF analysis leads to the identification of patterns of the rainy season and the associated mechanisms in terms of their energetics. The first combined EOF represents the northwest-southeast dipole of the precipitation between South and Central America, the South American Monsoon System (SAMS). The second combined EOF represents a synoptic pattern associated with the SACZ (South Atlantic convergence zone) and the third EOF is in spatial quadrature to the second EOF. The phase relationship of the EOFs, as computed from the principal components (PCs), suggests a nonlinear transition from the SACZ to the fully developed SAMS mode by November and between both components describing the SACZ by September-October (the rainy season onset). According to the LEC, the first mode is dominated by the eddy generation term at its maximum, the second by both baroclinic and eddy generation terms and the third by barotropic instability previous to the connection to the second mode by September-October. The predominance of the different LEC components at each phase of the SAMS can be used as an indicator of the onset of the rainy season in terms of physical processes, while the existence of the outstanding spectral peaks in the time dependence of the EOFs at the intraseasonal time scale could be used for monitoring purposes. Copyright (C) 2009 Royal Meteorological Society

Multivariate analysis of fresh-cut carambola slices stored under different temperatures

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)