45 resultados para Linear regression analysis

em CentAUR: Central Archive University of Reading - UK


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(ABR) is of fundamental importance to the investiga- tion of the auditory system behavior, though its in- terpretation has a subjective nature because of the manual process employed in its study and the clinical experience required for its analysis. When analyzing the ABR, clinicians are often interested in the identi- fication of ABR signal components referred to as Jewett waves. In particular, the detection and study of the time when these waves occur (i.e., the wave la- tency) is a practical tool for the diagnosis of disorders affecting the auditory system. In this context, the aim of this research is to compare ABR manual/visual analysis provided by different examiners. Methods: The ABR data were collected from 10 normal-hearing subjects (5 men and 5 women, from 20 to 52 years). A total of 160 data samples were analyzed and a pair- wise comparison between four distinct examiners was executed. We carried out a statistical study aiming to identify significant differences between assessments provided by the examiners. For this, we used Linear Regression in conjunction with Bootstrap, as a me- thod for evaluating the relation between the responses given by the examiners. Results: The analysis sug- gests agreement among examiners however reveals differences between assessments of the variability of the waves. We quantified the magnitude of the ob- tained wave latency differences and 18% of the inves- tigated waves presented substantial differences (large and moderate) and of these 3.79% were considered not acceptable for the clinical practice. Conclusions: Our results characterize the variability of the manual analysis of ABR data and the necessity of establishing unified standards and protocols for the analysis of these data. These results may also contribute to the validation and development of automatic systems that are employed in the early diagnosis of hearing loss.

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This paper derives some exact power properties of tests for spatial autocorrelation in the context of a linear regression model. In particular, we characterize the circumstances in which the power vanishes as the autocorrelation increases, thus extending the work of Krämer (2005). More generally, the analysis in the paper sheds new light on how the power of tests for spatial autocorrelation is affected by the matrix of regressors and by the spatial structure. We mainly focus on the problem of residual spatial autocorrelation, in which case it is appropriate to restrict attention to the class of invariant tests, but we also consider the case when the autocorrelation is due to the presence of a spatially lagged dependent variable among the regressors. A numerical study aimed at assessing the practical relevance of the theoretical results is included

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Multiple regression analysis is a statistical technique which allows to predict a dependent variable from m ore than one independent variable and also to determine influential independent variables. Using experimental data, in this study the multiple regression analysis is applied to predict the room mean velocity and determine the most influencing parameters on the velocity. More than 120 experiments for four different heat source locations were carried out in a test chamber with a high level wall mounted air supply terminal at air change rates 3-6 ach. The influence of the environmental parameters such as supply air momentum, room heat load, Archimedes number and local temperature ratio, were examined by two methods: a simple regression analysis incorporated into scatter matrix plots and multiple stepwise regression analysis. It is concluded that, when a heat source is located along the jet centre line, the supply momentum mainly influences the room mean velocity regardless of the plume strength. However, when the heat source is located outside the jet region, the local temperature ratio (the inverse of the local heat removal effectiveness) is a major influencing parameter.

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A study was designed to examine the relationships between protein, condensed tannin and cell wall carbohydrate content and composition and the nutritional quality of seven tropical legumes (Desmodium ovalifolium, Flemingia macrophylla, Leucaena leucocephala, L pallida, L macrophylla, Calliandra calothyrsus and Clitotia fairchildiana). Among the legume species studied, D ovalifolium showed the lowest concentration of nitrogen, while L leucocephala showed the highest. Fibre (NDF) content was lowest in C calothyrsus, L Leucocephala and L pallida and highest in L macrophylla, which had no measurable condensed tannins. The highest tannin concentration was found in C calothyrsus. Total non-structural polysaccharides (NSP) varied among legumes species (lowest in C calothyrsus and highest in D ovalifolium), and glucose and uronic acids were the most abundant carbohydrate constituents in all legumes. Total NSP losses were lowest in F macrophylla and highest in L leucocephala and L pallida. Gas accumulation and acetate and propionate levels were 50% less with F macrophylla and D ovalifolium as compared with L leucocephala. The highest levels of branched-chain fatty acids were observed with non-tanniniferous legumes, and negative concentrations were observed with some of the legumes with high tannin content (D ovalifolium and F macrophylla). Linear regression analysis showed that the presence of condensed tannins was more related to a reduction of the initial rate of gas production (0-48 h) than to the final amount of gas produced or the extent (144h) of dry matter degradation, which could be due to differences in tannin chemistry. Consequently, more attention should be given in the future to elucidating the impact of tannin structure on the nutritional quality of tropical forage legumes. (C) 2003 Society of Chemical Industry.

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Habitat-based statistical models relating patterns of presence and absence of species to habitat variables could be useful to resolve conservation-related problems and highlight the causes of population declines. In this paper, we apply such a modelling approach to an endemic amphibian, the Sardinian mountain newt Euproctus platycephalus, considered by IUCN a critically endangered species. Sardinian newts inhabit freshwater habitat in streams, small lakes and pools on the island of Sardinia (Italy). Reported declines of newt populations are not yet supported by quantitative data, however, they are perceived or suspected across the species' historical range. This study represents a first attempt trying to statistically relate habitat characteristics to Sardinian newt occurrence and persistence. Linear regression analysis revealed that newts are more likely to be found in sites with colder water temperature, less riparian vegetation and, marginally, absence of fish. The implications of the results for the conservation of the species are discussed, and suggestions for the short-term management of newt inhabited sites suggested. (C) 2003 Elsevier Ltd. All rights reserved.

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Although apolipoprotein AN (apoA-V) polymorphisms have been consistently associated with fasting triglyceride (TG) levels, their impact on postprandial lipemia remains relatively unknown. In this study, we investigate the impact of two common apoA-V polymorphisms (-1131 T>C and S19W) and apoA-V haplotypes on fasting and postprandial lipid metabolism in adults in the United Kingdom (n = 259). Compared with the wild-type TT, apoA-V -1131 TC heterozygotes had 15% (P = 0.057) and 21% (P = 0.002) higher fasting TG and postprandial TG area under the curve (AUC), respectively. Significant (P = 0.038) and nearly significant (P = 0.057) gender X genotype interactions were observed for fasting TG and TG AUC, with a greater impact of genotype in males. Lower HDL-cholesterol was associated with the rare TC genotype (P = 0.047). Significant linkage disequilibrium was found between the apoA-V -1131 T>C and the apoC-III 3238 C>G variants, with univariate analysis indicating an impact of this apoC-III single nucleotide polymorphism (SNP) on TG AUC (P = 0.015). However, in linear regression analysis, a significant independent association with TG AUC (P = 0.007) was only evident for the apoA-V -1131 T>C SNP, indicating a greater relative importance of the apoA-V genotype.

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Craloxylum formosum Dyer is consumed throughout the year as food and medicine in Thailand. It contains large amounts of chlorogenic acid and quinic acid derivatives. The antioxidative activity of the extract was studied in refined soybean oil coating on rice crackers without any seasoning. They were stored in accelerated oxidation conditions at 40 degrees C, 80% relative humidity (RH) in the dark for 18 days. The oxidative state of each sample was monitored by analyzing of the peroxide value (PV) and thiobarbituric acid reactive substances (TBARS) as well as by odor analysis by quantitative descriptive analysis (QDA). The C formosum extract was more effective than alpha-tocopherol due to metal ions present in the crackers, which resulted in alpha-tocopherol being less effective as an antioxidant. Sensory odor attributes of rice crackers were related more closely to TBARS than to PV values by linear regression analysis. The present study indicated that C. formosum extract was a promising source of a natural food antioxidant and was effective in inhibiting lipid oxidation in rice crackers.

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The recent global economic crisis is often associated with the development and pricing of mortgage-backed securities (i.e. MBSs) and underlying products (i.e. sub-prime mortgages). This work uses a rich database of MBS issues and represents the first attempt to price commercial MBSs (i.e. CMBSs) in the European market. Our results are consistent with research carried out in the US market and we find that bond-, mortgage-, real estate-related and multinational characteristics show different degrees of significance in explaining European CMBS spreads at issuance. Multiple linear regression analysis using a databank of CMBSs issued between 1997 and 2007 indicates a strong relationship with bond-related factors, followed by real estate and mortgage market conditions. We also find that multinational factors are significant, with country of issuance, collateral location and access to more liquid markets all being important in explaining the cost of secured funding for real estate companies. As floater coupon tranches tend to be riskier and exhibit higher spreads, we also estimate a model using this sub-set of data and results hold, hence reinforcing our findings. Finally, we estimate our model for both tranches A and B and find that real estate factors become relatively more important for the riskier investment products.

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A continuous tropospheric and stratospheric vertically resolved ozone time series, from 1850 to 2099, has been generated to be used as forcing in global climate models that do not include interactive chemistry. A multiple linear regression analysis of SAGE I+II satellite observations and polar ozonesonde measurements is used for the stratospheric zonal mean dataset during the well-observed period from 1979 to 2009. In addition to terms describing the mean annual cycle, the regression includes terms representing equivalent effective stratospheric chlorine (EESC) and the 11-yr solar cycle variability. The EESC regression fit coefficients, together with pre-1979 EESC values, are used to extrapolate the stratospheric ozone time series backward to 1850. While a similar procedure could be used to extrapolate into the future, coupled chemistry climate model (CCM) simulations indicate that future stratospheric ozone abundances are likely to be significantly affected by climate change, and capturing such effects through a regression model approach is not feasible. Therefore, the stratospheric ozone dataset is extended into the future (merged in 2009) with multimodel mean projections from 13 CCMs that performed a simulation until 2099 under the SRES (Special Report on Emission Scenarios) A1B greenhouse gas scenario and the A1 adjusted halogen scenario in the second round of the Chemistry-Climate Model Validation (CCMVal-2) Activity. The stratospheric zonal mean ozone time series is merged with a three-dimensional tropospheric data set extracted from simulations of the past by two CCMs (CAM3.5 and GISSPUCCINI)and of the future by one CCM (CAM3.5). The future tropospheric ozone time series continues the historical CAM3.5 simulation until 2099 following the four different Representative Concentration Pathways (RCPs). Generally good agreement is found between the historical segment of the ozone database and satellite observations, although it should be noted that total column ozone is overestimated in the southern polar latitudes during spring and tropospheric column ozone is slightly underestimated. Vertical profiles of tropospheric ozone are broadly consistent with ozonesondes and in-situ measurements, with some deviations in regions of biomass burning. The tropospheric ozone radiative forcing (RF) from the 1850s to the 2000s is 0.23Wm−2, lower than previous results. The lower value is mainly due to (i) a smaller increase in biomass burning emissions; (ii) a larger influence of stratospheric ozone depletion on upper tropospheric ozone at high southern latitudes; and possibly (iii) a larger influence of clouds (which act to reduce the net forcing) compared to previous radiative forcing calculations. Over the same period, decreases in stratospheric ozone, mainly at high latitudes, produce a RF of −0.08Wm−2, which is more negative than the central Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) value of −0.05Wm−2, but which is within the stated range of −0.15 to +0.05Wm−2. The more negative value is explained by the fact that the regression model simulates significant ozone depletion prior to 1979, in line with the increase in EESC and as confirmed by CCMs, while the AR4 assumed no change in stratospheric RF prior to 1979. A negative RF of similar magnitude persists into the future, although its location shifts from high latitudes to the tropics. This shift is due to increases in polar stratospheric ozone, but decreases in tropical lower stratospheric ozone, related to a strengthening of the Brewer-Dobson circulation, particularly through the latter half of the 21st century. Differences in trends in tropospheric ozone among the four RCPs are mainly driven by different methane concentrations, resulting in a range of tropospheric ozone RFs between 0.4 and 0.1Wm−2 by 2100. The ozone dataset described here has been released for the Coupled Model Intercomparison Project (CMIP5) model simulations in netCDF Climate and Forecast (CF) Metadata Convention at the PCMDI website (http://cmip-pcmdi.llnl.gov/).

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Wine production is largely governed by atmospheric conditions, such as air temperature and precipitation, together with soil management and viticultural/enological practices. Therefore, anthropogenic climate change is likely to have important impacts on the winemaking sector worldwide. An important winemaking region is the Portuguese Douro Valley, which is known by its world-famous Port Wine. The identification of robust relationships between atmospheric factors and wine parameters is of great relevance for the region. A multivariate linear regression analysis of a long wine production series (1932–2010) reveals that high rainfall and cool temperatures during budburst, shoot and inflorescence development (February-March) and warm temperatures during flowering and berry development (May) are generally favourable to high production. The probabilities of occurrence of three production categories (low, normal and high) are also modelled using multinomial logistic regression. Results show that both statistical models are valuable tools for predicting the production in a given year with a lead time of 3–4 months prior to harvest. These statistical models are applied to an ensemble of 16 regional climate model experiments following the SRES A1B scenario to estimate possible future changes. Wine production is projected to increase by about 10 % by the end of the 21st century, while the occurrence of high production years is expected to increase from 25 % to over 60 %. Nevertheless, further model development will be needed to include other aspects that may shape production in the future. In particular, the rising heat stress and/or changes in ripening conditions could limit the projected production increase in future decades.

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We introduce a novel technique in which linear regression analysis is applied to clusters of tracked cyclones to statistically assess the factors controlling cyclone development. We illustrate this technique by evaluating the differences between cyclones forming in the west and east North Atlantic (herein termed west and east Atlantic cyclones). Enhanced cyclone intensity 2 days after genesis is found to be associated with deeper upper-level troughs upstream of the cyclone center at the genesis time in both west and east Atlantic cyclones. However, whilst west Atlantic cyclones are also enhanced by the presence of strong fronts, east Atlantic cyclones are not. Instead, east Atlantic cyclones exhibit an enhancement when diabatically generated midlevel potential vorticity is present (with the enhancement being of approximately equal magnitude to that associated with the potential vorticity in the upper-level trough). This is consistent with the paradigm of latent heat release in the warm conveyor belt region playing an important role in the development of east Atlantic cyclones.