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Correlation Matrix (correlation + matrix)
Selected AbstractsPresent and past old-growth forests of the Lake Tahoe Basin, Sierra Nevada, USJOURNAL OF VEGETATION SCIENCE, Issue 4 2002M. Barbour Hickman (1993) for vascular plants; Furniss & Carolin (1977) for bark beetles; Hansen & Lewis (1997) for pathogens Abstract. We described 38 relictual old-growth stands , with data on the mortality, regeneration, floristic richness, fuel load and disease incidence in our study area in the Tahoe Basin of California and Nevada. The stands are within the lower and upper montane zones (1900,2400 m a.s.l.) and they are rare, occupying < 2% of the land in the Basin's watershed. Correlation matrices and ANOVAs of forest types and conifer species with environmental gradients revealed significant relationships with elevation, distance east of the Sierran crest, slope aspect, annual precipitation, date of complete snow melt, litter depth and degree of soil profile development. Pathogens, parasites and wood-boring insects were present on 23% of living trees; 16% of all trees were dead. We compared these stands to a reconstruction of pre-contact Basin forests and to ecologically analogous old-growth forests of Baja California that have never experienced fire suppression management. Currently, overstorey trees (> 180 yr old) in the Basin stands have ca. 33% cover, 54 m2.ha -1 basal area and 107 individuals.ha -1, values very similar to reconstructions of pre-contact Basin forests and to modern Baja California forests. Understorey trees (60,180 yr old), however, are several times more dense than historic levels and species composition is strongly dominated by A. concolor, regardless of the overstorey composition. The ratio of Pinus: Abies has increased , and the age structure of extant stands predicts that it will continue to increase , from approximately 1:1 in pre-contact time to 1:7 within the next century. Disease incidence and mortality in Baja forests were lower. Although we quantitatively defined current Basin old-growth forests , in terms of stand structure , we realize that our definition will differ from that of both past and future old-growth forests unless management protocols are changed. [source] FROM MICRO- TO MACROEVOLUTION THROUGH QUANTITATIVE GENETIC VARIATION: POSITIVE EVIDENCE FROM FIELD CRICKETSEVOLUTION, Issue 10 2004Mattieu Bégin Abstract . -Quantitative genetics has been introduced to evolutionary biologists with the suggestion that microevolution could be directly linked to macroevolutionary patterns using, among other parameters, the additive genetic variance/ covariance matrix (G) which is a statistical representation of genetic constraints to evolution. However, little is known concerning the rate and pattern of evolution of G in nature, and it is uncertain whether the constraining effect of G is important over evolutionary time scales. To address these issues, seven species of field crickets from the genera Gryllus and Teleogryllus were reared in the laboratory, and quantitative genetic parameters for morphological traits were estimated from each of them using a nested full-sibling family design. We used three statistical approaches (T method, Flury hierarchy, and Mantel test) to compare G matrices or genetic correlation matrices in a phylogenetic framework. Results showed that G matrices were generally similar across species, with occasional differences between some species. We suggest that G has evolved at a low rate, a conclusion strengthened by the consideration that part of the observed across-species variation in G can be explained by the effect of a genotype by environment interaction. The observed pattern of G matrix variation between species could not be predicted by either morphological trait values or phylogeny. The constraint hypothesis was tested by comparing the multivariate orientation of the reconstructed ancestral G matrix to the orientation of the across-species divergence matrix (D matrix, based on mean trait values). The D matrix mainly revealed divergence in size and, to a much smaller extent, in a shape component related to the ovipositor length. This pattern of species divergence was found to be predictable from the ancestral G matrix in agreement with the expectation of the constraint hypothesis. Overall, these results suggest that the G matrix seems to have an influence on species divergence, and that macroevolution can be predicted, at least qualitatively, from quantitative genetic theory. Alternative explanations are discussed. [source] Modularity of the rodent mandible: Integrating bones, muscles, and teethEVOLUTION AND DEVELOPMENT, Issue 6 2008Miriam Leah Zelditch Summary Several models explain how a complex integrated system like the rodent mandible can arise from multiple developmental modules. The models propose various integrating mechanisms, including epigenetic effects of muscles on bones. We test five for their ability to predict correlations found in the individual (symmetric) and fluctuating asymmetric (FA) components of shape variation. We also use exploratory methods to discern patterns unanticipated by any model. Two models fit observed correlation matrices from both components: (1) parts originating in same mesenchymal condensation are integrated, (2) parts developmentally dependent on the same muscle form an integrated complex as do those dependent on teeth. Another fits the correlations observed in FA: each muscle insertion site is an integrated unit. However, no model fits well, and none predicts the complex structure found in the exploratory analyses, best described as a reticulated network. Furthermore, no model predicts the correlation between proximal parts of the condyloid and coronoid, which can exceed the correlations between proximal and distal parts of the same process. Additionally, no model predicts the correlation between molar alveolus and ramus and/or angular process, one of the highest correlations found in the FA component. That correlation contradicts the basic premise of all five developmental models, yet it should be anticipated from the epigenetic effects of mastication, possibly the primary morphogenetic process integrating the jaw coupling forces generated by muscle contraction with those experienced at teeth. [source] The generalizability of the Buss,Perry Aggression QuestionnaireINTERNATIONAL JOURNAL OF METHODS IN PSYCHIATRIC RESEARCH, Issue 3 2007József Gerevich Abstract Aggressive and hostile behaviours and anger constitute an important problem across cultures. The Buss,Perry Aggression Questionnaire (AQ), a self-rating scale was published in 1992, and has quickly become the gold-standard for the measurement of aggression. The AQ scale has been validated extensively, but the validation focused on various narrowly selected populations, typically, on samples of college students. Individuals, however, who are at risk of displaying aggressive and hostile behaviours may come from a more general population. Therefore, it is important to investigate the scale's properties in such a population. The objective of this study was to examine the factorial structure and the psychometric properties of the AQ scale in a nationally representative sample of the Hungarian adult population. A representative sample of 1200 subjects was selected by a two-step procedure. The dimensionality and factorial composition of the AQ scale was investigated by exploratory and confirmatory factor analyses. Since spurious associations and increased factorial complexity can occur when the analysis fails to consider the inherently categorical nature of the item level data, this study, in contrast to most previous studies, estimated the correlation matrices subjected to factor analysis using the polychoric correlations. The resulting factors were validated via sociodemographic characteristics and psychopathological scales obtained from the respondents. The results showed that based on the distribution of factor loadings and factor correlations, in the entire nationally representative sample of 1200 adult subjects, from the original factor structure three of the four factors (Physical and Verbal Aggression and Hostility) showed a good replication whereas the fourth factor (Anger) replicated moderately well. Replication further improved when the sample was restricted in age, i.e. the analysis focused on a sample representing the younger age group, comparable to that used in the original Buss,Perry study. Similar to the Buss,Perry study, and other investigations of the AQ scale, younger age and male gender were robustly related to physical aggression. In addition, level of verbal aggression was different between the two genders (with higher severity in males) whereas hostility and anger were essentially the same in both genders. In conclusion, the current study based on a representantive sample of adult population lends support to the use of the AQ scale in the general population. The authors suggest to exclude from the AQ the two inverse items because of the low reliability of these items with regard to their hypothesized constructs. Copyright © 2007 John Wiley & Sons, Ltd. [source] The influence of experimental and model uncertainties on EXAFS resultsJOURNAL OF SYNCHROTRON RADIATION, Issue 2 2001Hermann Rossner We analyze EXAFS oscillations in k-space with the FEFF code to obtain main-shell distances R, and mean-square displacement parameters ,i2 for all single and multiple scattering paths i in the shells , up to a maximum shell radius Rmax. To quantify the uncertainty in the determination of these model parameters we take into account experimental errors and uncertainties connected with background subtraction, with the approximate handling of the electronic many-body problem in FEFF, and with the truncation of the multiple scattering series. The impact of these uncertainties on the R, and ,i2 is investigated in the framework of Bayesian methods. We introduce an a priori guess of these model parameters and consider two alternative strategies to control the weight of the a priori input relative to that of the experimental data. We can take a model parameter space of up to 250 dimensions. Optionally we can also fit the coordination numbers Nj (j,,) and the skewness of the distribution of the R, besides the R, and ,i2. The method is applied to 10K Cu K-edge and 300K Au L3 -edge data to obtain model parameters and their a posteriori error correlation matrices. [source] Reliability and validity of the Inventory of Functional Status after Childbirth when used in an Australian populationNURSING & HEALTH SCIENCES, Issue 3 2002Carol McVeigh RN Abstract This study presents the results of reliability and validity testing of the Inventory of Functional Status after Childbirth (IFSAC) when used in an Australian sample. Data were obtained from a culturally diverse group of 173 women residing in a regional city in New South Wales, Australia. Participants could read and write English, delivered healthy infants between 37 and 42 weeks gestation and experienced normal pregnancies, labors, and deliveries. The inventory and its five scales were assessed for reliability using Cronbach's coefficient , and construct validity using item-total correlation matrices. While three of the IFSAC scales performed well, two were problematic in this Australian population. With modification and updating, the clinical utility of IFSAC may be more fully realized. [source] Does Correlation Between Stock Returns Really Increase During Turbulent Periods?ECONOMIC NOTES, Issue 1 2001Francois Chesnay Correlations betwen international equity markets are often claimed to increase during periods of high volatility. Therefore the benefits of international diversification are reduced when they are most needed, i.e. during turbulent periods. This paper investigates the relationship between international correlation and stock-market turbulence. We estimate a multivariate Markov-switching model, in which the correlation matrix varies across regimes. Subsequently, we test the null hypothesis that correlations are regime-independent. Using weekly stock returns for the S&P, the DAX and the FTSE over the period 1988,99, we find that international correlations significantly increased during turbulent periods. (J.E.L.: C53, G15). [source] The impact of changing nicotine replacement therapy licensing laws in the United Kingdom: findings from the International Tobacco Control Four Country SurveyADDICTION, Issue 8 2009Lion Shahab ABSTRACT Aim To evaluate the impact of a new licence for some nicotine replacement therapy products (NRT) for cutting down to stop (CDTS) on changes in the pattern of NRT use. Design Quasi-experimental design comparing changes in NRT use across two waves of a population-based, replenished-panel, telephone survey conducted before and after the introduction of new licensing laws in the United Kingdom with changes in NRT use in three comparison countries (Australia, Canada and United States) without a licensing change. Participants A total of 7386 and 7013 smokers and recent ex-smokers participating in the 2004 and/or 2006/7 survey. Measurements Data were collected on demographic and smoking characteristics as well as NRT use and access. In order to account for interdependence resulting from some participants being present in both waves, generalized estimation equations with an exchangeable correlation matrix were used to assess within-country changes and linear and logistic regressions to assess between-country differences in adjusted analyses. Findings NRT use was more prevalent in the United Kingdom and increased across waves in all countries but no wave × country interaction was observed. There was no evidence that the licensing change increased the prevalence of CDTS or the use of NRT (irrespective of how it was accessed) for CDTS in the United Kingdom relative to comparison countries. There was also no evidence for a change in concurrent smoking and NRT use among smokers not attempting to stop in the United Kingdom relative to comparison countries. Conclusion The addition of the CDTS licence for some NRT products in the United Kingdom appears to have had very limited, if any, impact on NRT use in the first year after the licence change. [source] Temporal analysis of spatial covariance of SO2 in EuropeENVIRONMETRICS, Issue 4 2007Marco Giannitrapani Abstract In recent years, the number of applications of spatial statistics has enormously increased in environmental and ecological sciences. A typical problem is the sampling of a pollution field, with the common objective of spatial interpolation. In this paper, we present a spatial analysis across time, focusing on sulphur dioxide (SO2) concentrations monitored from 1990 to 2001 at 125 sites across Europe. Four different methods of trend estimation have been used, and comparisons among them are shown. Spherical, Exponential and Gaussian variograms have been fitted to the residuals and compared. Time series analyses of the range, sill and nugget have been undertaken and a suggestion for defining a unique spatial correlation matrix for the overall time period of analysis is proposed. Copyright © 2006 John Wiley & Sons, Ltd. [source] Candidate-gene association studies with pedigree data: Controlling for environmental covariatesGENETIC EPIDEMIOLOGY, Issue 4 2003S.L. Slager Abstract Case-control studies provide an important epidemiological tool to evaluate candidate genes. There are many different study designs available. We focus on a more recently proposed design, which we call a multiplex case-control (MCC) design. This design compares allele frequencies between related cases, each of whom are sampled from multiplex families, and unrelated controls. Since within-family genotype correlations will exist, statistical methods will need to take this into account. Moreover, there is a need to develop methods to simultaneously control for potential confounders in the analysis. Generalized estimating equations (GEE) are one approach to analyze this type of data; however, this approach can have singularity problems when estimating the correlation matrix. To allow for modeling of other covariates, we extend our previously developed method to a more general model-based approach. Our proposed methods use the score statistic, derived from a composite likelihood. We propose three different approaches to estimate the variance of this statistic. Under random ascertainment of pedigrees, score tests have correct type I error rates; however, pedigrees are not randomly ascertained. Thus, through simulations, we test the validity and power of the score tests under different ascertainment schemes, and an illustration of our methods, applied to data from a prostate cancer study, is presented. We find that our robust score statistic has estimated type I error rates within the expected range for all situations we considered whereas the other two statistics have inflated type I error rates under nonrandom ascertainment schemes. We also find GEE to fail at least 5% of the time for each simulation configuration; at times, the failure rate reaches above 80%. In summary, our robust method may be the only current regression analysis method available for MCC data. Genet Epidemiol 24:273,283, 2003. © 2003 Wiley-Liss, Inc. [source] Evaluating interactions between soil drainage and seedling performance in a restoration of Pinus sylvestris woodland, ScotlandGLOBAL ECOLOGY, Issue 2 2001M. D. Crowell Abstract 1,This paper evaluates the role of soil drainage in tree seedling performance at a site being restored from Calluna vulgaris moorland to Pinus sylvestris woodland, in Glen Affric, Scotland. The investigation focuses on the relationships between height of planted seedlings, type of ground vegetation and drainage conditions. 2,Slope, aspect, and soil depth were assessed as potential surrogates for direct measures of soil drainage, all of which were derived from digital terrain data. 3,Six variables related to drainage were recorded at 58 seedling locations and used in a factor analysis to understand links between soil moisture conditions, topographic variables and soil depth characteristics. 4,Factor analysis generated two factors that accounted for 70.5% of the variance in the correlation matrix of these variables: Factor 1 correlated strongly with variables that controlled peat accumulation and Factor 2 correlated strongly with topographic controls upon drainage patterns. 5,These two factors explained a significant amount of the variance in height of the Pinus seedlings planted at these locations. Significant differences were found between the factor scores associated with different types of ground vegetation, as well as between the seedling heights observed at locations with different vegetation types. 6,Multiple regressions were developed that indicated that slope, aspect, and soil depth were significant as independent variables in models where soil moisture content and aerobic soil depth were the dependent variables. [source] Altered small-world brain functional networks in children with attention-deficit/hyperactivity disorderHUMAN BRAIN MAPPING, Issue 2 2009Liang Wang Abstract In this study, we investigated the changes in topological architectures of brain functional networks in attention-deficit/hyperactivity disorder (ADHD). Functional magnetic resonance images (fMRI) were obtained from 19 children with ADHD and 20 healthy controls during resting state. Brain functional networks were constructed by thresholding the correlation matrix between 90 cortical and subcortical regions and further analyzed by applying graph theoretical approaches. Experimental results showed that, although brain networks of both groups exhibited economical small-world topology, altered functional networks were demonstrated in the brain of ADHD when compared with the normal controls. In particular, increased local efficiencies combined with a decreasing tendency in global efficiencies found in ADHD suggested a disorder-related shift of the topology toward regular networks. Additionally, significant alterations in nodal efficiency were also found in ADHD, involving prefrontal, temporal, and occipital cortex regions, which were compatible with previous ADHD studies. The present study provided the first evidence for brain dysfunction in ADHD from the viewpoint of global organization of brain functional networks by using resting-state fMRI. Hum Brain Mapp, 2009. © 2008 Wiley-Liss, Inc. [source] Focused principal component analysis: a promising approach for confirming findings of exploratory analysis?INTERNATIONAL JOURNAL OF METHODS IN PSYCHIATRIC RESEARCH, Issue 4 2001B. Falissard Abstract In many psychiatric studies, the objective is to describe and understand relationships between a large set of quantitative variables, with a particular interest in the relationship between one variable (often regarded as a response) and the others (often regarded as explanatory). This paper describes a new method to apply in such situations. It is based on principal components analysis (PCA). Like this technique, it conveys the structure of a correlation matrix into a low-dimensional diagram but, unlike PCA, it makes it possible to represent accurately the correlations of a given variable with the other variables (and even to test graphically the hypothesis that one of these correlations is equal to zero). Two examples in the field of psychiatry research are provided. Copyright © 2001 Whurr Publishers Ltd. [source] Exploratory second-order analyses for components and factorsJAPANESE PSYCHOLOGICAL RESEARCH, Issue 1 2002Haruhiko Ogasawara Abstract: Exploratory methods using second-order components and second-order common factors were proposed. The second-order components were obtained from the resolution of the correlation matrix of obliquely rotated first-order principal components. The standard errors of the estimates of the second-order component loadings were derived from an augmented information matrix with restrictions for the loadings and associated parameters. The second-order factor analysis proposed was similar to the classical method in that the factor correlations among the first-order factors were further resolved by the exploratory method of factor analysis. However, in this paper the second-order factor loadings were estimated by the generalized least squares using the asymptotic variance-covariance matrix for the first-order factor correlations. The asymptotic standard errors for the estimates of the second-order factor loadings were also derived. A numerical example was presented with simulated results. [source] A diagonal measure and a local distance matrix to display relations between objects and variables,JOURNAL OF CHEMOMETRICS, Issue 1 2010Gergely Tóth Abstract Proper permutation of data matrix rows and columns may result in plots showing striking information on the objects and variables under investigation. To control the permutation first, a diagonal matrix measureD was defined expressing the size relations of the matrix elements. D is essentially the absolute norm of a matrix where the matrix elements are weighted by their distance to the matrix diagonal. Changing the order of rows and columns increases or decreases D. Monte Carlo technique was used to achieve maximum D in the case of the object distance matrix or even minimal D in the case of the variable correlation matrix to get similar objects or variables close together. Secondly, a local distance matrix was defined, where an element reflects the distances of neighboring objects in a limited subspace of the variables. Due to the maximization of D in the local distance matrix by row and column changes of the original data matrix, the similar objects were arranged close to each other and simultaneously the variables responsible for their similarity were collected close to the diagonal part defined by these objects. This combination of the diagonal measure and the local distance matrix seems to be an efficient tool in the exploration of hidden similarities of a data matrix. Copyright © 2009 John Wiley & Sons, Ltd. [source] Regression by L1 regularization of smart contrasts and sums (ROSCAS) beats PLS and elastic net in latent variable modelJOURNAL OF CHEMOMETRICS, Issue 5 2009Cajo J. F. ter Braak Abstract This paper proposes a regression method, ROSCAS, which regularizes smart contrasts and sums of regression coefficients by an L1 penalty. The contrasts and sums are based on the sample correlation matrix of the predictors and are suggested by a latent variable regression model. The contrasts express the idea that a priori correlated predictors should have similar coefficients. The method has excellent predictive performance in situations, where there are groups of predictors with each group representing an independent feature that influences the response. In particular, when the groups differ in size, ROSCAS can outperform LASSO, elastic net, partial least squares (PLS) and ridge regression by a factor of two or three in terms of mean squared error. In other simulation setups and on real data, ROSCAS performs competitively. Copyright © 2009 John Wiley & Sons, Ltd. [source] Elephant distribution around a volcanic shield dominated by a mosaic of forest and savanna (Marsabit, Kenya)AFRICAN JOURNAL OF ECOLOGY, Issue 2 2009Shadrack M. Ngene Abstract We investigated the factors that influenced the distribution of the African elephant around a volcanic shield dominated by a mosaic of forest and savanna in northern Kenya. Data on elephant distribution were acquired from four female and five bull elephants, collared with satellite-linked geographical positioning system collars. Based on the eigenvalues (variances) of the correlation matrix, the six factors that contributed significantly to high total variances were distance from drinking water (24%), elevation (15%), shrubland (10%), forest (9%), distance from settlements (8%) and distance from minor roads (7%), contributing to 73% in the observed variation of the elephant distribution. The elephants were found at high forested elevations during the dry season but they moved to the lowlands characterized by shrubland during the wet season. Elevation acts as a proxy for the vegetation structure. The presence of elephants near permanent water points (13%) and seasonal rivers (11%) during the dry and wet seasons, respectively, demonstrates that water is the most important determinant of their distribution throughout the year. We conclude that the distribution of elephants in Marsabit Protected Area and its adjacent areas is influenced mainly by drinking water and vegetation structure. Résumé Nous avons étudié les facteurs qui influencent la distribution de l'éléphant africain autour d'un bouclier volcanique dominé par une mosaïque de forêt et de savane dans le nord du Kenya. Les données sur la distribution des éléphants furent acquises grâce à quatre femelles et cinq mâles équipés de colliers radio avec GPS par satellite. En se basant sur les valeurs propres (variances) de la matrice de corrélation, les six facteurs qui ont contribué significativement à de fortes variances totales étaient la distance par rapport à l'eau (24%), l'élévation (15%), la savane arbustive (10%), la forêt (9%), la distance par rapport à des installations (8%) et celle par rapport à des routes peu importantes (7%), qui contribuent donc ensemble à 73% de la variation observée dans la distribution de l'éléphant. Des éléphants se trouvaient sur de hautes élévations forestières pendant la saison sèche, mais ils se déplaçaient vers les terrains de basse altitude caractérisés par des broussailles pendant la saison des pluies. L'élévation sert de proxy à la structure de la végétation. La présence d'éléphants près des points d'eau permanents (13%) et des rivières saisonnières (11%) pendant la saison sèche et la saison des pluies respectivement montre que l'eau est le déterminant le plus important de leur distribution tout au long de l'année. Nous concluons que la distribution des éléphants dans la Marsabit Protected Area et dans les zones adjacentes est influencée principalement par la disponibilité de l'eau et la structure de la végétation. [source] Detecting Multidimensionality Due to Curricular DifferencesJOURNAL OF EDUCATIONAL MEASUREMENT, Issue 1 2003Christine E. DeMars Data were generated to simulate multidimensionality resulting from including two or four subtopics on a test. Each item was dependent on an ability trait due to instruction and learning, which was the same across all items, as well as an ability trait unique to the subtopic of the test (such as biology on a general science test). The eigenvalues of the item correlation matrix and Yen's Q3 were not greatly influenced by multidimensionality under conditions where the responses of a large proportion of students shared the influence of common instruction across subtopics. In contrast, Stout's T procedure was effective at detecting this type of multidimensionality, unless the subtopic abilities were correlated. [source] Relationships between psychological climate perceptions and work outcomes: a meta-analytic reviewJOURNAL OF ORGANIZATIONAL BEHAVIOR, Issue 4 2003Christopher P. Parker In this study, meta-analytic procedures were used to examine the relationships between individual-level (psychological) climate perceptions and work outcomes such as employee attitudes, psychological well-being, motivation, and performance. Our review of the literature generated 121 independent samples in which climate perceptions were measured and analyzed at the individual level. These studies document considerable confusion regarding the constructs of psychological climate, organizational climate, and organizational culture and reveal a need for researchers to use terminology that is consistent with their level of measurement, theory, and analysis. Our meta-analytic findings indicate that psychological climate, operationalized as individuals' perceptions of their work environment, does have significant relationships with individuals' work attitudes, motivation, and performance. Structural equation modeling analyses of the meta-analytic correlation matrix indicated that the relationships of psychological climate with employee motivation and performance are fully mediated by employees' work attitudes. We also found that the James and James (1989) PCg model could be extended to predict the impact of work environment perceptions on employee attitudes, motivation, and performance. Despite the number of published individual-level climate studies that we found, there is a need for more research using standardized measures so as to enable analyses of the organizational and contextual factors that might moderate the effects of psychological climate perceptions. Finally, we argue for a molar theory of psychological climate that is rooted in the psychological processes by which individuals make meaning or their work experiences. Copyright © 2003 John Wiley & Sons, Ltd. [source] BUSINESS COMMUNITY STRUCTURES AND URBAN REGIMES: A COMPARATIVE ANALYSISJOURNAL OF URBAN AFFAIRS, Issue 4 2007MARK DE SOCIO ABSTRACT:,Regime theorists often present business interests as coherent and unified communities with unitary interests. A central principle of regime theory, however, is that business elites tend to occupy privileged positions within regime coalitions because of the scope of resources and expertise they command and cities require for economic development and/or fiscal solvency. Cities are generally home to a wide range of business activities operating at various scales, and business elites representing various corporations in different economic sectors arguably command different kinds of resources and expertise that are functional to the economic activities with which they are affiliated. Various mixes of business elites representing different economic activities might therefore produce differentially biased input regarding urban policy-making and affect the types of regime coalitions that cities develop.Utilizing compilations of interlocking directorates among major organizations across three sectors, profiles of the corporate and social community structures of 24 U.S. cities are generated and a correlation matrix comprised of business and social organizational categories is produced. Factor analysis of the correlation matrix identifies three separate mixes of corporate and social organizational categories that generally conform to descriptions of developmental, caretaker, and progressive regime typologies. These three factors serve as prototypes of the three broad regime types and their corporate community structures. Correlations of the 24 cities with each of the three regime prototypes generally match their regime types as identified through previous case studies. Variations in regime types among cities might therefore be attributed to varying degrees of diversity in the kinds of corporations headquartered or located within them. Closer attention to the economic base of cities,the producers, after all, of local business elites,may reveal internal biases and/or material predisposition towards some urban policies over others by local business elites in relation to the economic activities with which they are linked. [source] On the noise correlation matrix for multiple radio frequency coilsMAGNETIC RESONANCE IN MEDICINE, Issue 2 2007Ryan Brown Abstract Noise correlation between multiple receiver coils is discussed using principles of statistical physics. Using the general fluctuation-dissipation theorem we derive the prototypic correlation formula originally determined by Redpath (Magn Res Med 1992;24:85,89), which states that correlation of current spectral noise depends on the real part of the inverse impedance matrix at a given frequency. A distinct correlation formula is also derived using the canonical partition function, which states that correlation of total current noise over the entire frequency spectrum depends on the inverse inductance matrix. The Kramers-Kronig relation is used to equate the inverse inductance matrix to the spectral integral of the inverse impedance matrix, implying that the total noise is equal to the summation of the spectral noise over the entire frequency spectrum. Previous conflicting arguments on noise correlation may be reconciled by differentiating between spectral and total noise correlation. These theoretical derivations are verified experimentally using two-coil arrays. Magn Reson Med 58:218,224, 2007. © 2007 Wiley-Liss, Inc. [source] Relationships between milk characteristics and somatic cell score in milk from primiparous browsing goatsANIMAL SCIENCE JOURNAL, Issue 5 2010Giuseppe M. VACCA ABSTRACT To determine milk yield and composition, total microbic count (TMC) and somatic cell count (SCC) of browsing goats throughout the first lactation, 100 goats of Sarda breed, equally distributed in four flocks (F1, F2, F3 and F4), were selected. They were exclusively fed pasture and hand-milked once daily. Individual milk samples and daily milk yield were taken from each goat at monthly intervals, from March to July. Milk samples were analyzed for: total protein, fat, lactose, urea, freezing point (FP), pH, TMC and SCC. The data was subjected to analysis of variance and to correlation matrix. On the whole, in all the flocks, milk yield showed the highest production in April and May. Fat content increased (P < 0.01) throughout the lactation. Protein content showed the lowest value (P < 0.01) in June (4.15%). Urea and pH values were fluctuating. FP was lower (P < 0.01) at the start of lactation (,0.562 Hortvet degrees). TMC log10 values were low, considering the hand milking and inadequacy of facilities on the farms. SCC increased (P < 0.01) throughout the lactation and, on the whole, SCC and TMC were not correlated. [source] Determining best complete subsets of specimens and characters for multivariate morphometric studies in the presence of large amounts of missing dataBIOLOGICAL JOURNAL OF THE LINNEAN SOCIETY, Issue 2 2006RICHARD E. STRAUSS Missing data are frequent in morphometric studies of both fossil and recent material. A common method of addressing the problem of missing data is to omit combinations of characters and specimens from subsequent analyses; however, omitting different subsets of characters and specimens can affect both the statistical robustness of the analyses and the resulting biological interpretations. We describe a method of examining all possible subsets of complete data and of scoring each subset by the ,condition' (ratio of first eigenvalue to second, or of second to first, depending on context) of the corresponding covariance or correlation matrix, and subsequently choosing the submatrix that either optimizes one of these criteria or matches the estimated condition of the original data matrix. We then describe an extension of this method that can be used to choose the ,best' characters and specimens for which some specified proportion of missing data can be estimated using standard imputation techniques such as the expectation-maximization algorithm or multiple imputation. The methods are illustrated with published and unpublished data sets on fossil and extant vertebrates. Although these problems and methods are discussed in the context of conventional morphometric data, they are applicable to many other kinds of data matrices. © 2006 The Linnean Society of London, Biological Journal of the Linnean Society, 2006, 88, 309,328. [source] FDR Control by the BH Procedure for Two-Sided Correlated Tests with Implications to Gene Expression Data AnalysisBIOMETRICAL JOURNAL, Issue 1 2007Anat Reiner-Benaim Abstract The multiple testing problem attributed to gene expression analysis is challenging not only by its size, but also by possible dependence between the expression levels of different genes resulting from co-regulations of the genes. Furthermore, the measurement errors of these expression levels may be dependent as well since they are subjected to several technical factors. Multiple testing of such data faces the challenge of correlated test statistics. In such a case, the control of the False Discovery Rate (FDR) is not straightforward, and thus demands new approaches and solutions that will address multiplicity while accounting for this dependency. This paper investigates the effects of dependency between bormal test statistics on FDR control in two-sided testing, using the linear step-up procedure (BH) of Benjamini and Hochberg (1995). The case of two multiple hypotheses is examined first. A simulation study offers primary insight into the behavior of the FDR subjected to different levels of correlation and distance between null and alternative means. A theoretical analysis follows in order to obtain explicit upper bounds to the FDR. These results are then extended to more than two multiple tests, thereby offering a better perspective on the effect of the proportion of false null hypotheses, as well as the structure of the test statistics correlation matrix. An example from gene expression data analysis is presented. (© 2007 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim) [source] Artificial Neural Networks and the Study of the Psychoactivity of Cannabinoid CompoundsCHEMICAL BIOLOGY & DRUG DESIGN, Issue 6 2010Káthia M. Honório Cannabinoid compounds have widely been employed because of its medicinal and psychotropic properties. These compounds are isolated from Cannabis sativa (or marijuana) and are used in several medical treatments, such as glaucoma, nausea associated to chemotherapy, pain and many other situations. More recently, its use as appetite stimulant has been indicated in patients with cachexia or AIDS. In this work, the influence of several molecular descriptors on the psychoactivity of 50 cannabinoid compounds is analyzed aiming one obtain a model able to predict the psychoactivity of new cannabinoids. For this purpose, initially, the selection of descriptors was carried out using the Fisher's weight, the correlation matrix among the calculated variables and principal component analysis. From these analyses, the following descriptors have been considered more relevant: ELUMO (energy of the lowest unoccupied molecular orbital), Log P (logarithm of the partition coefficient), VC4 (volume of the substituent at the C4 position) and LP1 (Lovasz,Pelikan index, a molecular branching index). To follow, two neural network models were used to construct a more adequate model for classifying new cannabinoid compounds. The first model employed was multi-layer perceptrons, with algorithm back-propagation, and the second model used was the Kohonen network. The results obtained from both networks were compared and showed that both techniques presented a high percentage of correctness to discriminate psychoactive and psychoinactive compounds. However, the Kohonen network was superior to multi-layer perceptrons. [source] Pattern hunting in climate: a new method for finding trends in gridded climate dataINTERNATIONAL JOURNAL OF CLIMATOLOGY, Issue 1 2007A. Hannachi Abstract Trends are very important in climate research and are ubiquitous in the climate system. Trends are usually estimated using simple linear regression. Given the complexity of the system, trends are expected to have various features such as global and local characters. It is therefore important to develop methods that permit a systematic decomposition of climate data into different trend patterns and remaining no-trend patterns. Empirical orthogonal functions and closely related methods, widely used in atmospheric science, are unable in general to capture trends because they are not devised for that purpose. The present paper presents a novel method capable of systematically capturing trend patterns from gridded data. The method is based on an eigenanalysis of the covariance/correlation matrix obtained using correlations between time positions of the sorted data, and trends are associated with the leading nondegenerate eigenvalues. Application to simple low-dimensional time series models and reanalyses data are presented and discussed. Copyright © 2006 Royal Meteorological Society. [source] | |||||||||||||||||||||||||||||||||||||