948 resultados para Linear regression analysis
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This paper discusses models, associations and causation in psychiatry. The different types of association (linear, positive, negative, exponential, partial, U shaped relationship, hidden and spurious) between variables involved in mental disorders are presented as well as the use of multiple regression analysis to disentangle interrelatedness amongst multiple variables. A useful model should have internal consistency, external validity and predictive power; be dynamic in order to accommodate new sound knowledge; and should fit facts rather than they other way around. It is argued that whilst models are theoretical constructs they also convey a style of reasoning and can change clinical practice. Cause and effect are complex phenomena in that the same cause can yield different effects. Conversely, the same effect can have a different range of causes. In mental disorders and human behaviour there is always a chain of events initiated by the indirect and remote cause; followed by intermediate causes; and finally the direct and more immediate cause. Causes of mental disorders are grouped as those: (i) which are necessary and sufficient; (ii) which are necessary but not sufficient; and (iii) which are neither necessary nor sufficient, but when present increase the risk for mental disorders.
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Tese de Doutoramento em Engenharia Civil.
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Dissertação de mestrado integrado em Engenharia Civil
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Dissertação de mestrado em Finanças
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Dissertação de mestrado em Ecologia
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OBJECTIVE - To analyze the trends in risk of death due to cardiovascular diseases in the northern, northeastern, southern, southeastern, and central western Brazilian geographic regions from 1979 to 1996. METHODS - Data on mortality due to cardiovascular, cardiac ischemic, and cerebrovascular diseases in 5 Brazilian geographic regions were obtained from the Ministry of Health. Population estimates for the time period from 1978 to 1996 in the 5 Brazilian geographic regions were calculated by interpolation with the Lagrange method, based on the census data from 1970, 1980, 1991, and the population count of 1996, for each age bracket and sex. Trends were analyzed with the multiple linear regression model. RESULTS - Cardiovascular diseases showed a declining trend in the southern, southeastern, and northern Brazilian geographic regions in all age brackets and for both sexes. In the northeastern and central western regions, an increasing trend in the risk of death due to cardiovascular diseases occurred, except for the age bracket from 30 to 39 years, which showed a slight reduction. This resulted from the trends of cardiac ischemic and cerebrovascular diseases. The analysis of the trend in the northeastern and northern regions was impaired by the great proportion of poorly defined causes of death. CONCLUSION - The risk of death due to cardiovascular, cerebrovascular, and cardiac ischemic diseases decreased in the southern and southeastern regions, which are the most developed regions in the country, and increased in the least developed regions, mainly in the central western region.
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Natural mineral waters (still), effervescent natural mineral waters (sparkling) and aromatized waters with fruit-flavors (still or sparkling) are an emerging market. In this work, the capability of a potentiometric electronic tongue, comprised with lipid polymeric membranes, to quantitatively estimate routinely quality physicochemical parameters (pH and conductivity) as well as to qualitatively classify water samples according to the type of water was evaluated. The study showed that a linear discriminant model, based on 21 sensors selected by the simulated annealing algorithm, could correctly classify 100 % of the water samples (leave-one out cross-validation). This potential was further demonstrated by applying a repeated K-fold cross-validation (guaranteeing that at least 15 % of independent samples were only used for internal-validation) for which 96 % of correct classifications were attained. The satisfactory recognition performance of the E-tongue could be attributed to the pH, conductivity, sugars and organic acids contents of the studied waters, which turned out in significant differences of sweetness perception indexes and total acid flavor. Moreover, the E-tongue combined with multivariate linear regression models, based on sub-sets of sensors selected by the simulated annealing algorithm, could accurately estimate waters pH (25 sensors: R 2 equal to 0.99 and 0.97 for leave-one-out or repeated K-folds cross-validation) and conductivity (23 sensors: R 2 equal to 0.997 and 0.99 for leave-one-out or repeated K-folds cross-validation). So, the overall satisfactory results achieved, allow envisaging a potential future application of electronic tongue devices for bottled water analysis and classification.
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Tese de Doutoramento em Engenharia Industrial e de Sistemas.
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Background: Heart failure is a severe complication associated with doxorubicin (DOX) use. Strain, assessed by two-dimensional speckle tracking (2D-STE), has been shown to be useful in identifying subclinical ventricular dysfunction. Objectives: a) To investigate the role of strain in the identification of subclinical ventricular dysfunction in patients who used DOX; b) to investigate determinants of strain response in these patients. Methods: Cross-sectional study with 81 participants: 40 patients who used DOX ±2 years before the study and 41 controls. All participants had left ventricular ejection fraction (LVEF) ≥55%. Total dose of DOX was 396mg (242mg/ms2). The systolic function of the LV was evaluated by LVEF (Simpson), as well as by longitudinal (εLL), circumferential (εCC), and radial (εRR) strains. Multivariate linear regression (MLR) analysis was performed using εLL (model 1) and εCC (model 2) as dependent variables. Results: Systolic and diastolic blood pressure values were higher in the control group (p < 0.05). εLL was lower in the DOX group (-12.4 ±2.6%) versus controls (-13.4 ± 1.7%; p = 0.044). The same occurred with εCC: -12.1 ± 2.7% (DOX) versus -16.7 ± 3.6% (controls; p < 0.001). The S’ wave was shorter in the DOX group (p = 0.035). On MLR, DOX was an independent predictor of reduced εCC (B = -4.429, p < 0.001). DOX (B = -1.289, p = 0.012) and age (B = -0.057, p = 0.029) were independent markers of reduced εLL. Conclusion: a) εLL, εCC and the S’ wave are reduced in patients who used DOX ±2 years prior to the study despite normal LVEF, suggesting the presence of subclinical ventricular dysfunction; b) DOX was an independent predictor of reduced εCC; c) prior use of DOX and age were independent markers of reduced εLL.
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Background:Previous reports have inferred a linear relationship between LDL-C and changes in coronary plaque volume (CPV) measured by intravascular ultrasound. However, these publications included a small number of studies and did not explore other lipid markers.Objective:To assess the association between changes in lipid markers and regression of CPV using published data.Methods:We collected data from the control, placebo and intervention arms in studies that compared the effect of lipidlowering treatments on CPV, and from the placebo and control arms in studies that tested drugs that did not affect lipids. Baseline and final measurements of plaque volume, expressed in mm3, were extracted and the percentage changes after the interventions were calculated. Performing three linear regression analyses, we assessed the relationship between percentage and absolute changes in lipid markers and percentage variations in CPV.Results:Twenty-seven studies were selected. Correlations between percentage changes in LDL-C, non-HDL-C, and apolipoprotein B (ApoB) and percentage changes in CPV were moderate (r = 0.48, r = 0.47, and r = 0.44, respectively). Correlations between absolute differences in LDL-C, non‑HDL-C, and ApoB with percentage differences in CPV were stronger (r = 0.57, r = 0.52, and r = 0.79). The linear regression model showed a statistically significant association between a reduction in lipid markers and regression of plaque volume.Conclusion:A significant association between changes in different atherogenic particles and regression of CPV was observed. The absolute reduction in ApoB showed the strongest correlation with coronary plaque regression.
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Background:Left atrial volume (LAV) is a predictor of prognosis in patients with heart failure.Objective:We aimed to evaluate the determinants of LAV in patients with dilated cardiomyopathy (DCM).Methods:Ninety patients with DCM and left ventricular (LV) ejection fraction ≤ 0.50 were included. LAV was measured with real-time three-dimensional echocardiography (eco3D). The variables evaluated were heart rate, systolic blood pressure, LV end-diastolic volume and end-systolic volume and ejection fraction (eco3D), mitral inflow E wave, tissue Doppler e´ wave, E/e´ ratio, intraventricular dyssynchrony, 3D dyssynchrony index and mitral regurgitation vena contracta. Pearson´s coefficient was used to identify the correlation of the LAV with the assessed variables. A multiple linear regression model was developed that included LAV as the dependent variable and the variables correlated with it as the predictive variables.Results:Mean age was 52 ± 11 years-old, LV ejection fraction: 31.5 ± 8.0% (16-50%) and LAV: 39.2±15.7 ml/m2. The variables that correlated with the LAV were LV end-diastolic volume (r = 0.38; p < 0.01), LV end-systolic volume (r = 0.43; p < 0.001), LV ejection fraction (r = -0.36; p < 0.01), E wave (r = 0.50; p < 0.01), E/e´ ratio (r = 0.51; p < 0.01) and mitral regurgitation (r = 0.53; p < 0.01). A multivariate analysis identified the E/e´ ratio (p = 0.02) and mitral regurgitation (p = 0.02) as the only independent variables associated with LAV increase.Conclusion:The LAV is independently determined by LV filling pressures (E/e´ ratio) and mitral regurgitation in DCM.
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The authors studied the effects of calving time, season and time elapsed after calving on milk production of the Holstein Friesian Breed of the "Escola Superior de Agricultura "Luiz de Queiroz" (Piracicaba, Brasil), 180 lactation periods of 300 days were studied, with 15 calvings in each month. Statistical analysis of the data proved : 1. That calving in May, June, July or August, that is, in the driest months, the cows give a milk production 17,3% larger than calving in December, January, February, March or April. August is the best month for calving, and February is the worst. 2. Spring is the most favorable, and Autumn the most unfavorable season for milk production. 3. The decrease of milk production during the lactation period depends largely on calving time. But, on the whole, linear regression can be used as a good aproximation, with a correlation coefficient r = - 0,9926 and a monthly decrease, per month elapsed after calving, of 8,06 percent of the general mean. 4. Diagram 1 shows the effects of calving month on milk production. The limits of 5%, 1% and l%o of probabilities are given there.
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The plastral spotting variation in the chelid turtle Phrynops hilarii (Duméril & Bibron, 1835) in relation to sex, size, and geographic procedence of individuals was analyzed. States for qualitative characters were analyzed using non-parametric tests. Quantitative characters (shell and scute measurements) were standardized for body size by linear regression against carapace length, and were subjected to principal components analysis and canonical discriminant function analysis. Results suggest that increased plastral spotting is a polymorphic ontogenetic trait in P. hilarii. Neither hatchlings nor juveniles have plastral pattern moderately or heavily pigmented. The simplest pattern, however, may persist without changes in some adults. There are no differences between sexes. The spatial distribution of the plastral pattern is not ordered latitudinally or longitudinally, showing no relationship with gradients of elevation, temperature, or precipitation. This pattern trait lacks of taxonomic significance. The morphometric analysis failed to reveal any character of diagnostic utility in the plastron to support the possibility that these patterns correspond to different sympatric taxa.
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This study has aims to determine the age and to estimate the growth parameters using scales of the species. Individuals of Piaractus mesopotamicus (Holmberg, 1887) used in this study were captured in the commercial fishery conducted in the region, along the year 2006. The model selected to express the growth of the species was the von Bertalanffy Sl= Sl∞*[1-exp-k(t-to)]. To determine if scales are suitable for studying the growth of pacu, we analyzed the relation between standard length (Sl) and the radius of the scales through linear regression. The period of annuli formation was determined analyzing the variations in the marginal increment and evaluating the consistency of the readings through the analysis of the coefficient of variations (CVs) for the average standard lengths of each age (number of rings) observed in the scales. The relationship between Ls of the fish and the radius of the scales showed that scales can be used to study the age and growth of P. mesopotamicus (R= 0.79). CVs were always below 20%, demonstrating the consistency of the readings. Annuli formation occurred in February, probably related to trophic migration that occurs in this month in the region. Equations that represents the growth in length obtained for P. mesopotamicus are Sl=50.00*[1-exp-0.18(t-(-3.00)] for males and Sl=59.23*[1-exp-0.14(t-(-3.36)] for females. The growth parameters obtained in this study were lower compared to other studies previously conducted for the same species and can related to overexploitation that species is submitted by fishing in the region. These values show also that females of pacu attain greater asymptotic length than males that growth faster.
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Inductive learning aims at finding general rules that hold true in a database. Targeted learning seeks rules for the predictions of the value of a variable based on the values of others, as in the case of linear or non-parametric regression analysis. Non-targeted learning finds regularities without a specific prediction goal. We model the product of non-targeted learning as rules that state that a certain phenomenon never happens, or that certain conditions necessitate another. For all types of rules, there is a trade-off between the rule's accuracy and its simplicity. Thus rule selection can be viewed as a choice problem, among pairs of degree of accuracy and degree of complexity. However, one cannot in general tell what is the feasible set in the accuracy-complexity space. Formally, we show that finding out whether a point belongs to this set is computationally hard. In particular, in the context of linear regression, finding a small set of variables that obtain a certain value of R2 is computationally hard. Computational complexity may explain why a person is not always aware of rules that, if asked, she would find valid. This, in turn, may explain why one can change other people's minds (opinions, beliefs) without providing new information.