952 resultados para Dynamic data set visualization


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OBJECTIVE: To better understand the structure of the Patient Assessment of Chronic Illness Care (PACIC) instrument. More specifically to test all published validation models, using one single data set and appropriate statistical tools. DESIGN: Validation study using data from cross-sectional survey. PARTICIPANTS: A population-based sample of non-institutionalized adults with diabetes residing in Switzerland (canton of Vaud). MAIN OUTCOME MEASURE: French version of the 20-items PACIC instrument (5-point response scale). We conducted validation analyses using confirmatory factor analysis (CFA). The original five-dimension model and other published models were tested with three types of CFA: based on (i) a Pearson estimator of variance-covariance matrix, (ii) a polychoric correlation matrix and (iii) a likelihood estimation with a multinomial distribution for the manifest variables. All models were assessed using loadings and goodness-of-fit measures. RESULTS: The analytical sample included 406 patients. Mean age was 64.4 years and 59% were men. Median of item responses varied between 1 and 4 (range 1-5), and range of missing values was between 5.7 and 12.3%. Strong floor and ceiling effects were present. Even though loadings of the tested models were relatively high, the only model showing acceptable fit was the 11-item single-dimension model. PACIC was associated with the expected variables of the field. CONCLUSIONS: Our results showed that the model considering 11 items in a single dimension exhibited the best fit for our data. A single score, in complement to the consideration of single-item results, might be used instead of the five dimensions usually described.

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Extreme weather events can lead to immediate catastrophic mortality. Due to their rare occurrence, however, the long-term impacts of such events for ecological processes are unclear. We examined the effect of extreme winters on barn owl (Tyto alba) survival and reproduction in Switzerland over a 68-year period (approximately 20 generations). This long-term data set allowed us to compare events that occurred only once in several decades to more frequent events. Winter harshness explained 17 and 49% of the variance in juvenile and adult survival, respectively, and the two harshest winters were associated with major population crashes caused by simultaneous low juvenile and adult survival. These two winters increased the correlation between juvenile and adult survival from 0.63 to 0.69. Overall, survival decreased non-linearly with increasing winter harshness in adults, and linearly in juveniles. In contrast, brood size was not related to the harshness of the preceding winter. Our results thus reveal complex interactions between climate and demography. The relationship between weather and survival observed during regular years is likely to underestimate the importance of climate variation for population dynamics.

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The vast territories that have been radioactively contaminated during the 1986 Chernobyl accident provide a substantial data set of radioactive monitoring data, which can be used for the verification and testing of the different spatial estimation (prediction) methods involved in risk assessment studies. Using the Chernobyl data set for such a purpose is motivated by its heterogeneous spatial structure (the data are characterized by large-scale correlations, short-scale variability, spotty features, etc.). The present work is concerned with the application of the Bayesian Maximum Entropy (BME) method to estimate the extent and the magnitude of the radioactive soil contamination by 137Cs due to the Chernobyl fallout. The powerful BME method allows rigorous incorporation of a wide variety of knowledge bases into the spatial estimation procedure leading to informative contamination maps. Exact measurements (?hard? data) are combined with secondary information on local uncertainties (treated as ?soft? data) to generate science-based uncertainty assessment of soil contamination estimates at unsampled locations. BME describes uncertainty in terms of the posterior probability distributions generated across space, whereas no assumption about the underlying distribution is made and non-linear estimators are automatically incorporated. Traditional estimation variances based on the assumption of an underlying Gaussian distribution (analogous, e.g., to the kriging variance) can be derived as a special case of the BME uncertainty analysis. The BME estimates obtained using hard and soft data are compared with the BME estimates obtained using only hard data. The comparison involves both the accuracy of the estimation maps using the exact data and the assessment of the associated uncertainty using repeated measurements. Furthermore, a comparison of the spatial estimation accuracy obtained by the two methods was carried out using a validation data set of hard data. Finally, a separate uncertainty analysis was conducted that evaluated the ability of the posterior probabilities to reproduce the distribution of the raw repeated measurements available in certain populated sites. The analysis provides an illustration of the improvement in mapping accuracy obtained by adding soft data to the existing hard data and, in general, demonstrates that the BME method performs well both in terms of estimation accuracy as well as in terms estimation error assessment, which are both useful features for the Chernobyl fallout study.

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The shrews of the Sorex araneus group, characterized by the sexual chromosome complex XY1, Y2 have been intensively studied by morphological, karyotypical, and biochemical analyses. Nevertheless, the phylogenetic relationships among the species belonging to the araneus complex are still under debate, as different approaches gave often contradictory results. In this paper, partial nucleotide sequences of the mitochondrial DNA cytochrome b gene (1011 bp) were determined for 6 species of the araneus group from Eurasia and North America. We also included in the data set the sequences of Sorex samniticus, whose relationships with the araneus group remain controversial. Three other species representing two major karyological groups were also examined. Both parsimony and distance trees strongly support the monophyly of the araneus group. Sorex sumniticus is significantly more closely related to the araneus complex than to the other species included in the analysis. Based on the branching pattern within the araneus group, an attempt has been made to reconstruct the colonization history of the Holarctic region.

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We analyze crash data collected by the Iowa Department of Transportation using Bayesian methods. The data set includes monthly crash numbers, estimated monthly traffic volumes, site length and other information collected at 30 paired sites in Iowa over more than 20 years during which an intervention experiment was set up. The intervention consisted in transforming 15 undivided road segments from four-lane to three lanes, while an additional 15 segments, thought to be comparable in terms of traffic safety-related characteristics were not converted. The main objective of this work is to find out whether the intervention reduces the number of crashes and the crash rates at the treated sites. We fitted a hierarchical Poisson regression model with a change-point to the number of monthly crashes per mile at each of the sites. Explanatory variables in the model included estimated monthly traffic volume, time, an indicator for intervention reflecting whether the site was a “treatment” or a “control” site, and various interactions. We accounted for seasonal effects in the number of crashes at a site by including smooth trigonometric functions with three different periods to reflect the four seasons of the year. A change-point at the month and year in which the intervention was completed for treated sites was also included. The number of crashes at a site can be thought to follow a Poisson distribution. To estimate the association between crashes and the explanatory variables, we used a log link function and added a random effect to account for overdispersion and for autocorrelation among observations obtained at the same site. We used proper but non-informative priors for all parameters in the model, and carried out all calculations using Markov chain Monte Carlo methods implemented in WinBUGS. We evaluated the effect of the four to three-lane conversion by comparing the expected number of crashes per year per mile during the years preceding the conversion and following the conversion for treatment and control sites. We estimated this difference using the observed traffic volumes at each site and also on a per 100,000,000 vehicles. We also conducted a prospective analysis to forecast the expected number of crashes per mile at each site in the study one year, three years and five years following the four to three-lane conversion. Posterior predictive distributions of the number of crashes, the crash rate and the percent reduction in crashes per mile were obtained for each site for the months of January and June one, three and five years after completion of the intervention. The model appears to fit the data well. We found that in most sites, the intervention was effective and reduced the number of crashes. Overall, and for the observed traffic volumes, the reduction in the expected number of crashes per year and mile at converted sites was 32.3% (31.4% to 33.5% with 95% probability) while at the control sites, the reduction was estimated to be 7.1% (5.7% to 8.2% with 95% probability). When the reduction in the expected number of crashes per year, mile and 100,000,000 AADT was computed, the estimates were 44.3% (43.9% to 44.6%) and 25.5% (24.6% to 26.0%) for converted and control sites, respectively. In both cases, the difference in the percent reduction in the expected number of crashes during the years following the conversion was significantly larger at converted sites than at control sites, even though the number of crashes appears to decline over time at all sites. Results indicate that the reduction in the expected number of sites per mile has a steeper negative slope at converted than at control sites. Consistent with this, the forecasted reduction in the number of crashes per year and mile during the years after completion of the conversion at converted sites is more pronounced than at control sites. Seasonal effects on the number of crashes have been well-documented. In this dataset, we found that, as expected, the expected number of monthly crashes per mile tends to be higher during winter months than during the rest of the year. Perhaps more interestingly, we found that there is an interaction between the four to three-lane conversion and season; the reduction in the number of crashes appears to be more pronounced during months, when the weather is nice than during other times of the year, even though a reduction was estimated for the entire year. Thus, it appears that the four to three-lane conversion, while effective year-round, is particularly effective in reducing the expected number of crashes in nice weather.

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Do the contests with the largest prizes attract the most able contestants? Towhat extent do contestants avoid competition? In this paper, we show, theoreticallyand empirically, that the distribution of abilities plays a crucial role in determiningcontest choice. Sorting exists only when the proportion of high-ability contestantsis sufficiently small. As this proportion increases, contestants shy away from competitionand sorting decreases, such that, reverse sorting becomes a possibility. Wetest our theoretical predictions using a large panel data set containing contest choiceover three decades. We use exogenous variation in the participation of highly-ablecompetitors to provide empirical evidence for the relationship among prizes, competition,and sorting.

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Objective Psychogenic non-epileptic seizures (PNES) are paroxysmal events that, in contrast to epileptic seizures, are related to psychological causes without the presence of epileptiform EEG changes. Recent models suggest a multifactorial basis for PNES. A potentially paramount, but currently poorly understood factor is the interplay between psychiatric features and a specific vulnerability of the brain leading to a clinical picture that resembles epilepsy. Hypothesising that functional cerebral network abnormalities may predispose to the clinical phenotype, the authors undertook a characterisation of the functional connectivity in PNES patients. Methods The authors analysed the whole-head surface topography of multivariate phase synchronisation (MPS) in interictal high-density EEG of 13 PNES patients as compared with 13 age- and sex-matched controls. MPS mapping reduces the wealth of dynamic data obtained from high-density EEG to easily readable synchronisation maps, which provide an unbiased overview of any changes in functional connectivity associated with distributed cortical abnormalities. The authors computed MPS maps for both Laplacian and common-average-reference EEGs. Results In a between-group comparison, only patchy, non-uniform changes in MPS survived conservative statistical testing. However, against the background of these unimpressive group results, the authors found widespread inverse correlations between individual PNES frequency and MPS within the prefrontal and parietal cortices. Interpretation PNES appears to be associated with decreased prefrontal and parietal synchronisation, possibly reflecting dysfunction of networks within these regions.

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Network formation within the BRITE--EURAM program is investigated.Wedescribe the role of the hub of the network, which is defined as the setofmain contractors that account for most of the participations. We studytheeffects that the conflict of objectives within European research fundingbetween pre-competitive research vs. European cohesion has on theformationof networks and on the relationship between different partnersof the network. \\A panel data set is constructed including the second and third frameworkof theBrite--Euram program. A model of joint production of research results isusedto test for changes in the behavior of partners within the twoframeworks. \\The main findings are that participations are very concentrated, that isasmall group of institutions account for most of the participations, butgoingfrom the second to the third framework the presence of subcontractorsand singleparticipants increases substantially. This result is reinforced by the factthat main contractors receive smaller spill-ins within networks, butspill-insincrease from the second to the third framework.

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Searching for a suitable breeding site is an important decision in the life of most animals. The decisions where to settle and how far to travel before doing so depend on many factors. Individual differences in dispersal distance could result from different strategies (e.g. specialists versus generalists), which might result in similar reproductive success in different habitats, or different competitive abilities to acquire a territory close to the natal site. The barn owl is polymorphic in melanic coloration, which is associated with many physiological and behavioural traits such as habitat choice, stress response and docility, raising the possibility that the coloration is also related to dispersal. We studied natal dispersal (from rearing site to site of first breeding attempt) and breeding dispersal (from one breeding site to the next) in barn owls using a long-term data set. Darker reddish individuals moved further than paler individuals during natal dispersal, but not during breeding dispersal. A cross-fostering experiment showed that the colour of the biological and foster parents had no influence on dispersal distance. The distance dispersed by parents and same-sex offspring was correlated, whereas natal and breeding dispersal were not repeatable within individuals, indicating that they are two different processes. Given that the distance travelled in natal dispersal appears to be heritable, the underlying genes might be coupled to those related to coloration. We discuss hypotheses to explain the potential adaptive function of the link between coloration and natal dispersal.

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Strepsirhines comprise 10 living or recently extinct families, ≥50% of extant primate families. Their phylogenetic relationships have been intensively studied, but common topologies have only recently emerged; e.g. all recent reconstructions link the Lepilemuridae and Cheirogaleidae. The position of the indriids, however, remains uncertain, and molecular studies have placed them as the sister to every clade except Daubentonia, the preferred sister group of morphologists. The node subtending Afro-Asian lorisids has been similarly elusive. We probed these phylogenetic inconsistencies using a test data set including 20 strepsirhine taxa and 2 outgroups represented by 3,543 mtDNA base pairs, and 43 selected morphological characters, subjecting the data to maximum parsimony, maximum likelihood and Bayesian inference analyses, and reconstructing topology and node ages jointly from the molecular data using relaxed molecular clock analyses. Our permutations yielded compatible but not identical evolutionary histories, and currently popular techniques seem unable to deal adequately with morphological data. We investigated the influence of morphological characters on tree topologies, and examined the effect of taxon sampling in two experiments: (1) we removed the molecular data only for 5 endangered Malagasy taxa to simulate 'extinction leaving a fossil record'; (2) we removed both the sequence and morphological data for these taxa. Topologies were affected more by the inclusion of morphological data only, indicating that palaeontological studies that involve inserting a partial morphological data set into a combined data matrix of extant species should be interpreted with caution. The gap of approximately 10 million years between the daubentoniid divergence and those of the other Malagasy families deserves more study. The apparently contemporaneous divergence of African and non-daubentoniid Malagasy families 40-30 million years ago may be related to regional plume-induced uplift followed by a global period of cooling and drying. © 2013 S. Karger AG, Basel.

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We study the effect of providing relative performance feedback information onperformance, when individuals are rewarded according to their absolute performance. Anatural experiment that took place in a high school offers an unusual opportunity to testthis effect in a real-effort setting. For one year only, students received information thatallowed them to know whether they were performing above (below) the class average aswell as the distance from this average. We exploit a rich panel data set and find that theprovision of this information led to an increase of 5% in students grades. Moreover, theeffect was significant for the whole distribution. However, once the information wasremoved, the effect disappeared. To rule out the concern that the effect may beartificially driven by teachers within the school, we verify our results using nationallevel exams (externally graded) for the same students, and the effect remains.

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In spite of increasing representation of women in politics, little is known about their impact onpolicies. Comparing outcomes of parliaments with different shares of female members does not identifytheir causal impact because of possible differences in the underlying electorate. This paper usesa unique data set on voting decisions to sheds new light on gender gaps in policy making. Ouranalysis focuses on Switzerland, where all citizens can directly decide on a broad range of policiesin referendums and initiatives. We show that there are large gender gaps in the areas of health,environmental protection, defense spending and welfare policy which typically persist even conditionalon socio-economic characteristics. We also find that female policy makers have a substantial effect onthe composition of public spending, but a small effect on the overall size of government.

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Aim This study used data from temperate forest communities to assess: (1) five different stepwise selection methods with generalized additive models, (2) the effect of weighting absences to ensure a prevalence of 0.5, (3) the effect of limiting absences beyond the environmental envelope defined by presences, (4) four different methods for incorporating spatial autocorrelation, and (5) the effect of integrating an interaction factor defined by a regression tree on the residuals of an initial environmental model. Location State of Vaud, western Switzerland. Methods Generalized additive models (GAMs) were fitted using the grasp package (generalized regression analysis and spatial predictions, http://www.cscf.ch/grasp). Results Model selection based on cross-validation appeared to be the best compromise between model stability and performance (parsimony) among the five methods tested. Weighting absences returned models that perform better than models fitted with the original sample prevalence. This appeared to be mainly due to the impact of very low prevalence values on evaluation statistics. Removing zeroes beyond the range of presences on main environmental gradients changed the set of selected predictors, and potentially their response curve shape. Moreover, removing zeroes slightly improved model performance and stability when compared with the baseline model on the same data set. Incorporating a spatial trend predictor improved model performance and stability significantly. Even better models were obtained when including local spatial autocorrelation. A novel approach to include interactions proved to be an efficient way to account for interactions between all predictors at once. Main conclusions Models and spatial predictions of 18 forest communities were significantly improved by using either: (1) cross-validation as a model selection method, (2) weighted absences, (3) limited absences, (4) predictors accounting for spatial autocorrelation, or (5) a factor variable accounting for interactions between all predictors. The final choice of model strategy should depend on the nature of the available data and the specific study aims. Statistical evaluation is useful in searching for the best modelling practice. However, one should not neglect to consider the shapes and interpretability of response curves, as well as the resulting spatial predictions in the final assessment.

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This study represents the most extensive analysis of batch-to-batch variations in spray paint samples to date. The survey was performed as a collaborative project of the ENFSI (European Network of Forensic Science Institutes) Paint and Glass Working Group (EPG) and involved 11 laboratories. Several studies have already shown that paint samples of similar color but from different manufacturers can usually be differentiated using an appropriate analytical sequence. The discrimination of paints from the same manufacturer and color (batch-to-batch variations) is of great interest and these data are seldom found in the literature. This survey concerns the analysis of batches from different color groups (white, papaya (special shade of orange), red and black) with a wide range of analytical techniques and leads to the following conclusions. Colored batch samples are more likely to be differentiated since their pigment composition is more complex (pigment mixtures, added pigments) and therefore subject to variations. These variations may occur during the paint production but may also occur when checking the paint shade in quality control processes. For these samples, techniques aimed at color/pigment(s) characterization (optical microscopy, microspectrophotometry (MSP), Raman spectroscopy) provide better discrimination than techniques aimed at the organic (binder) or inorganic composition (fourier transform infrared spectroscopy (FTIR) or elemental analysis (SEM - scanning electron microscopy and XRF - X-ray fluorescence)). White samples contain mainly titanium dioxide as a pigment and the main differentiation is based on the binder composition (Csingle bondH stretches) detected either by FTIR or Raman. The inorganic composition (elemental analysis) also provides some discrimination. Black samples contain mainly carbon black as a pigment and are problematic with most of the spectroscopic techniques. In this case, pyrolysis-GC/MS represents the best technique to detect differences. Globally, Py-GC/MS may show a high potential of discrimination on all samples but the results are highly dependent on the specific instrumental conditions used. Finally, the discrimination of samples when data was interpreted visually as compared to statistically using principal component analysis (PCA) yielded very similar results. PCA increases sensitivity and could perform better on specific samples, but one first has to ensure that all non-informative variation (baseline deviation) is eliminated by applying correct pre-treatments. Statistical treatments can be used on a large data set and, when combined with an expert's opinion, will provide more objective criteria for decision making.

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In this article an empirical analyse of farming costs is performed withinthe frame of the activity based costing, employing a panel data set ofCatalan farms. One the main conclusions of the study is that there islimited association for transaction and farm costs, especially in indirectcosts. Direct and indirect costs are mainly driven by volume production.