883 resultados para Fractional regression models


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Relationships between surface sediment diatom assemblages and lake trophic status were studied in 50 Canadian Precambrian Shield lakes in the Muskoka-Haliburton and southern Ontario regions. The purpose of this study was to develop mathematical regression models to infer lake trophic status from diatom assemblage data. To achieve this goal, however, additional investigations dealing with the evaluation of lake trophic status and the autecological features of key diatom species were carried out. Because a unifying index and classification for lake trophic status was not available, a new multiple index was developed in this study, by the computation of the physical, chemical and biological data from 85 south Ontario lakes. By using the new trophic parameter, the lake trophic level (TL) was determined: TL = 1.37 In[1 +(TP x Chl-a / SD)], where, TP=total phosphorus, Chl-a=chlorophyll-a and SD=Secchi depth. The boundaries between 7 lake trophic categories (Ultra-oligotrophic lakes: 0-0.24; Oligotrophic lakes: 0.241-1.8; Oligomesotrophic lakes: 1.813.0; Mesotrophic lakes: 3.01-4.20; Mesoeutrophic lakes: 4.21-5.4; Eutrophic lakes: 5.41-10 and Hyper-eutrophic lakes: above 10) were established. The new trophic parameter was more convenient for management of water quality, communication to the public and comparison with other lake trophic status indices than many of the previously published indices because the TL index attempts to Increase understanding of the characteristics of lakes and their comprehensive trophic states. It is more reasonable and clear for a unifying determination of true trophic states of lakes. Diatom specIes autecology analysis was central to this thesis. However, the autecological relationship of diatom species and lake trophic status had not previously been well documented. Based on the investigation of the diatom composition and variety of species abundance in 30 study lakes, the distribution optima of diatom species were determined. These determinations were based on a quantitative method called "weighted average" (Charles 1985). On this basis, the diatom species were classified into five trophic categories (oligotrophic, oligomesotrophic, mesotrophic, mesoeutrophic and eutrophic species groups). The resulting diatom trophic status autecological features were used in the regressIon analysis between diatom assemblages and lake trophic status. When the TL trophic level values of the 30 lakes were regressed against their fi ve corresponding diatom trophic groups, the two mathematical equations for expressing the assumed linear relationship between the diatom assemblages composition were determined by (1) uSIng a single regression technique: Trophic level of lake (TL) = 2.643 - 7.575 log (Index D) (r = 0.88 r2 = 0.77 P = 0.0001; n = 30) Where, Index D = (0% + OM% + M%)/(E% + ME% + M%); 4 (2) uSIng a' multiple regressIon technique: TL=4.285-0.076 0%- 0.055 OM% - 0.026 M% + 0.033 ME% + 0.065 E% (r=0.89, r2=0.792, P=O.OOOl, n=30) There was a significant correlation between measured and diatom inferred trophic levels both by single and multiple regressIon methods (P < 0.0001, n=20), when both models were applied to another 20 test lakes. Their correlation coefficients (r2 ) were also statistically significant (r2 >0.68, n=20). As such, the two transfer function models between diatoms and lake trophic status were validated. The two models obtained as noted above were developed using one group of lakes and then tested using an entirely different group of lakes. This study indicated that diatom assemblages are sensitive to lake trophic status. As indicators of lake trophic status, diatoms are especially useful in situations where no local trophic information is available and in studies of the paleotrophic history of lakes. Diatom autecological information was used to develop a theory assessing water quality and lake trophic status.

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Hom's (2008) model of coaching effectiveness proposes a series of direct relationships between the beliefs and values of coaches, their behaviours, and the perceptions of their athletes. One specific area of coaching behaviour that is in need of more research is their use of psychological skills training (PSn. The purpose of this study was to examine the relationship between the beliefs and behaviours of curling coaches with respect to PST, and the perceptions of their athletes. In collaboration with the Canadian Curling Association, data was collected from a national sample of 115 curling teams with varying levels of competition and experience. One hundred and fifteen coaches completed PST attitude (SPA-RC-revised) and behaviour (MSQ-revised) measures, while 403 athletes completed two perception measures (CCS and S-CI). Interclass correlation coefficients (ICC) were calculated to ensure intra-team consistency. All ICCs were positive, ranging from r =.39 to .56, and significant at the p < .01 level. A series of multiple regressions were performed. Three of the four regression models were significant, with coaches' PST behaviours accounting for 16% of the variance in athletes' evaluation of their coaches' competencies (GeC). The models for athletes' PhysicalSport Confidence (P-SC) and Cognitive-Sport Confidence (C-SC) accounted for 15% and 36% of the variation, with GCC and coaches' PST behaviours both being significant predictors of the models. After statistically controlling the influence of GCC, coaches' PST behaviours accounted for 3% and 26% of the variation in athletes P-SC and C-SC. These results provide partial support for Hom's (2008) model of coaching effectiveness, and offer new insight into the benefits of coaches' use of sport psychology-related training behaviours.

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Background: The purpose of this study was to examine the relationships between physical activity and healthy eating behaviour with the participant's motives and goals for each health behaviour. Methods: Participants (N 121; 93.2% female) enrolled in commercial weightloss programs at the time of data collection, completed self-reported instruments using a web-based interface that were in accordance with Deci and Ryan's (2002) Self-Determination Theory (SDT). Results: Multiple linear regression models revealed that motivation and goals collectively accounted for between 0.21 to 0.29 percent and 0.03 to 0.16 percent of the variance in physical and healthy eating behaviours in this sample. In general, goals regarding either behaviour did not appear to have strong predictive relationships with each health behaviour beyond the contributions of motives. Discussion: Overall, findings from this study suggest that motives seem to mattermore than goals for both physical activity and healthy eating behaviour in clientele of commercial weight-loss programs. Therefore commercial weight-loss program implementers may want to consider placing more attention on motives I than goals for their clientele when designing weight-loss and weight-maintenance initiatives.

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Previous research shows discrepant findings between youth leisure programming (before and after school programs, structured summer program, day camp, overnight camp), academic performance and other youth developmental outcomes. Studies underscores the importance of family, community and school social capital in educational success of youth, investigation of peer social capital in the leisure context and academic performance outcomes is limited. This study uses a sample of 10 and 11 year olds (N=1764) from the Canadian National Longitudinal Survey of Children and Youth (NLSCY) Cycle 6, to study the association between youth leisure programming, peer social capital and academic performance. Ordinal logistic regression models consistently showed a positive association between overnight camp and academic performance even after controlling for determinants of health, and measures of family, school and community social capital. Similarly, the measure of peer social capital was positively associated with academic performance. Most importantly, the interaction between overnight camp participation and peer social capital was significantly associated with academic performance. Study findings, highlight overnight camp opportunities and peer social

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To examine the association between sleep disorders, obesity status, and the risk of diabetes in adults, a total of 3668 individuals aged 40+ years fromtheNHANES 2009-2010 withoutmissing information on sleep-related questions,measurements related to diabetes, and BMI were included in this analysis. Subjects were categorized into three sleep groups based on two sleep questions: (a) no sleep problems; (b) sleep disturbance; and (c) sleep disorder. Diabetes was defined as having one of a diagnosis from a physician; an overnight fasting glucose > 125 mg/dL; Glycohemoglobin > 6.4%; or an oral glucose tolerance test > 199mg/dL. Overall, 19% of subjects were diabetics, 37% were obese, and 32% had either sleep disturbance or sleep disorder. Using multiple logistic regression models adjusting for covariates without including BMI, the odds ratios (OR, (95% CI)) of diabetes were 1.40 (1.06, 1.84) and 2.04 (1.40, 2.95) for those with sleep disturbance and with sleep disorder, respectively. When further adjusting for BMI, the ORs were similar for those with sleep disturbance 1.36 (1.06, 1.73) but greatly attenuated for those with sleep disorders (1.38 [0.95, 2.00]). In conclusion, the impact of sleep disorders on diabetes may be explained through the individuals’ obesity status.

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In this thesis I assess the individual and joint predictive associations and effects between multiple motivation and well-being concepts. In particular, three pairs of motivation concepts (intrinsic/extrinsic, approach/avoidance, and eudaimonic/hedonic) are assessed simultaneously at two levels of analysis (disposition and goal) and examined in relation to two types of well-being (eudaimonic and hedonic) in two studies, one correlational and the other experimental. Study 1: Using a correlational design, participants (N = 325, M age = 19.10, 87% female) completed self-report measures assessing six motivation and two well-being concepts. Exploratory factor analyses were used to assess patterns of associations among the motivational constructs. Results indicated that constructs displaying conceptual and empirical similarities co-occur, particularly, intrinsic, approach and eudaimonic motivation. Regression models were used to assess predictive relations between the motivational constructs and well-being. Both types of well-being were predicted by approach and avoidance dispositions, and hedonic goals. Additionally, eudaimonic well-being was uniquely predicted by eudaimonic dispositions and goals, and intrinsic dispositions; and hedonic well-being was uniquely predicted by extrinsic dispositions and approach goals. The patterns of associations among motivational constructs, and similarities and differences in the ways they predict each type of well-being, are discussed. Study 2: Using an experimental design, participants (N = 447, M age = 19.30, 88% female) were randomly assigned to one of eight experimental conditions, each involving a manipulation aimed at priming combinations of the three pairs of motivational constructs at the goal level. Participants then completed measures of both types of well-being. ANOVAs were used to assess the main effects and interactions of experimental condition for each of the three pairs of motivational constructs on well-being. Main effects of experimental conditions were non-significant. However, results indicated that focus on each of the three pairs of motivational constructs predicted well-being and that the manipulation impacted well-being indirectly, through experimentally-shifted motivational focus. Few interactions emerged. Implications for future experimental research and the conceptual integration of motivation and well-being constructs are discussed. In conclusion, Studies 1 and 2 inform the motivation and well-being fields in novel ways and provide preliminary steps towards studying these fields from an integrated and comprehensive motivational framework.

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We assess the predictive ability of three VPIN metrics on the basis of two highly volatile market events of China, and examine the association between VPIN and toxic-induced volatility through conditional probability analysis and multiple regression. We examine the dynamic relationship on VPIN and high-frequency liquidity using Vector Auto-Regression models, Granger Causality tests, and impulse response analysis. Our results suggest that Bulk Volume VPIN has the best risk-warning effect among major VPIN metrics. VPIN has a positive association with market volatility induced by toxic information flow. Most importantly, we document a positive feedback effect between VPIN and high-frequency liquidity, where a negative liquidity shock boosts up VPIN, which, in turn, leads to further liquidity drain. Our study provides empirical evidence that reflects an intrinsic game between informed traders and market makers when facing toxic information in the high-frequency trading world.

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The study aim was to investigate the relationship between factors related to personal cancer history and lung cancer risk as well as assess their predictive utility. Characteristics of interest included the number, anatomical site(s), and age of onset of previous cancer(s). Data from the Prostate, Lung, Colorectal and Ovarian Screening (PLCO) Cancer Screening Trial (N = 154,901) and National Lung Screening Trial (N = 53,452) were analysed. Logistic regression models were used to assess the relationships between each variable of interest and 6-year lung cancer risk. Predictive utility was assessed through changes in area-under-the-curve (AUC) after substitution into the PLCOall2014 lung cancer risk prediction model. Previous lung, uterine and oral cancers were strongly and significantly associated with elevated 6-year lung cancer risk after controlling for confounders. None of these refined measures of personal cancer history offered more predictive utility than the simple (yes/no) measure already included in the PLCOall2014 model.

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Soil-transmitted helminth (STH) infections are endemic in Honduras, but their prevalence according to the levels of poverty in the population has not been examined. The present cross-sectional study is aimed to determine the role of different levels of poverty in STH prevalence and infection intensity as well as the potential associations of STH infections with malnutrition and anemia. Research participants were children attending a medical brigade serving remote communities in Northern Honduras in June 2014. Demographic data were obtained, and poverty levels were determined using the unsatisfied basic needs method. STH infections were investigated by the Kato-Katz method; hemoglobin concentrations were determined with the HemoCue system; and stunting, thinness, and underweight were determined by anthropometry. Data were analyzed using descriptive statistics and univariate and multivariable logistic regression models. Among 130 children who participated in this study, a high prevalence (69.2%) of parasitism was found and the poorest children were significantly more infected than those living in less poor communities (79.6% vs. 61.8%; P = 0.030). Prevalence rates of Trichuris trichiura, Ascaris lumbricoides, and hookworms were 69.2%, 12.3%, and 3.85%, respectively. In total, 69% of children had anemia and 30% were stunted. Households’ earthen floor and lack of latrines were associated with infection. Greater efforts should be made to reduce STH prevalence and improve overall childhood health, in particular, among the poorest children lacking the basic necessities of life.

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This paper proposes finite-sample procedures for testing the SURE specification in multi-equation regression models, i.e. whether the disturbances in different equations are contemporaneously uncorrelated or not. We apply the technique of Monte Carlo (MC) tests [Dwass (1957), Barnard (1963)] to obtain exact tests based on standard LR and LM zero correlation tests. We also suggest a MC quasi-LR (QLR) test based on feasible generalized least squares (FGLS). We show that the latter statistics are pivotal under the null, which provides the justification for applying MC tests. Furthermore, we extend the exact independence test proposed by Harvey and Phillips (1982) to the multi-equation framework. Specifically, we introduce several induced tests based on a set of simultaneous Harvey/Phillips-type tests and suggest a simulation-based solution to the associated combination problem. The properties of the proposed tests are studied in a Monte Carlo experiment which shows that standard asymptotic tests exhibit important size distortions, while MC tests achieve complete size control and display good power. Moreover, MC-QLR tests performed best in terms of power, a result of interest from the point of view of simulation-based tests. The power of the MC induced tests improves appreciably in comparison to standard Bonferroni tests and, in certain cases, outperforms the likelihood-based MC tests. The tests are applied to data used by Fischer (1993) to analyze the macroeconomic determinants of growth.

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In the literature on tests of normality, much concern has been expressed over the problems associated with residual-based procedures. Indeed, the specialized tables of critical points which are needed to perform the tests have been derived for the location-scale model; hence reliance on available significance points in the context of regression models may cause size distortions. We propose a general solution to the problem of controlling the size normality tests for the disturbances of standard linear regression, which is based on using the technique of Monte Carlo tests.

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Conditional heteroskedasticity is an important feature of many macroeconomic and financial time series. Standard residual-based bootstrap procedures for dynamic regression models treat the regression error as i.i.d. These procedures are invalid in the presence of conditional heteroskedasticity. We establish the asymptotic validity of three easy-to-implement alternative bootstrap proposals for stationary autoregressive processes with m.d.s. errors subject to possible conditional heteroskedasticity of unknown form. These proposals are the fixed-design wild bootstrap, the recursive-design wild bootstrap and the pairwise bootstrap. In a simulation study all three procedures tend to be more accurate in small samples than the conventional large-sample approximation based on robust standard errors. In contrast, standard residual-based bootstrap methods for models with i.i.d. errors may be very inaccurate if the i.i.d. assumption is violated. We conclude that in many empirical applications the proposed robust bootstrap procedures should routinely replace conventional bootstrap procedures for autoregressions based on the i.i.d. error assumption.

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Ce texte propose des méthodes d’inférence exactes (tests et régions de confiance) sur des modèles de régression linéaires avec erreurs autocorrélées suivant un processus autorégressif d’ordre deux [AR(2)], qui peut être non stationnaire. L’approche proposée est une généralisation de celle décrite dans Dufour (1990) pour un modèle de régression avec erreurs AR(1) et comporte trois étapes. Premièrement, on construit une région de confiance exacte pour le vecteur des coefficients du processus autorégressif (φ). Cette région est obtenue par inversion de tests d’indépendance des erreurs sur une forme transformée du modèle contre des alternatives de dépendance aux délais un et deux. Deuxièmement, en exploitant la dualité entre tests et régions de confiance (inversion de tests), on détermine une région de confiance conjointe pour le vecteur φ et un vecteur d’intérêt M de combinaisons linéaires des coefficients de régression du modèle. Troisièmement, par une méthode de projection, on obtient des intervalles de confiance «marginaux» ainsi que des tests à bornes exacts pour les composantes de M. Ces méthodes sont appliquées à des modèles du stock de monnaie (M2) et du niveau des prix (indice implicite du PNB) américains

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Objectif : Examiner l’association entre la consommation alimentaire de caroténoïdes (β-carotène, α-carotène, β-cryptoxanthine, lutéine/zéaxanthine, lycopène) et de vitamine C et le risque de cancer du poumon, selon le sexe, l’intensité de tabagisme et le sous-type histologique de la tumeur. Méthodes : Les données proviennent d’une étude cas-témoins menée à Montréal, Canada. Des entrevues ont été effectuées auprès de 1 105 cas incidents de cancer du poumon et 1 449 témoins issus de la population générale. Leur fréquence de consommation moyenne de 49 fruits et légumes deux ans auparavant a été convertie en apports en antioxydants. Les rapports de cotes (RC) et les intervalles de confiance (IC) à 95% caractérisant l’association entre les antioxydants et le risque de cancer du poumon ont été estimés à l’aide de modèles de régression logistique et polytomée, en tenant compte de facteurs de confusion potentiels. Résultats : Une consommation élevée en antioxydants était généralement associée à une diminution du risque de cancer du poumon de l’ordre de 30%. Un effet protecteur a été observé chez les hommes et les femmes, pour les non fumeurs, les fumeurs quelque soit l’intensité de tabagisme, ainsi que pour les carcinomes à petites cellules, épidermoïde et l’adénocarcinome. Conclusions : Plusieurs antioxydants alimentaires protégeraient du cancer du poumon. Les efforts de prévention bénéficieraient de cibler la promotion de la consommation de fruits et de légumes riches en caroténoïdes et en vitamine C.

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Contexte. Les études cas-témoins sont très fréquemment utilisées par les épidémiologistes pour évaluer l’impact de certaines expositions sur une maladie particulière. Ces expositions peuvent être représentées par plusieurs variables dépendant du temps, et de nouvelles méthodes sont nécessaires pour estimer de manière précise leurs effets. En effet, la régression logistique qui est la méthode conventionnelle pour analyser les données cas-témoins ne tient pas directement compte des changements de valeurs des covariables au cours du temps. Par opposition, les méthodes d’analyse des données de survie telles que le modèle de Cox à risques instantanés proportionnels peuvent directement incorporer des covariables dépendant du temps représentant les histoires individuelles d’exposition. Cependant, cela nécessite de manipuler les ensembles de sujets à risque avec précaution à cause du sur-échantillonnage des cas, en comparaison avec les témoins, dans les études cas-témoins. Comme montré dans une étude de simulation précédente, la définition optimale des ensembles de sujets à risque pour l’analyse des données cas-témoins reste encore à être élucidée, et à être étudiée dans le cas des variables dépendant du temps. Objectif: L’objectif général est de proposer et d’étudier de nouvelles versions du modèle de Cox pour estimer l’impact d’expositions variant dans le temps dans les études cas-témoins, et de les appliquer à des données réelles cas-témoins sur le cancer du poumon et le tabac. Méthodes. J’ai identifié de nouvelles définitions d’ensemble de sujets à risque, potentiellement optimales (le Weighted Cox model and le Simple weighted Cox model), dans lesquelles différentes pondérations ont été affectées aux cas et aux témoins, afin de refléter les proportions de cas et de non cas dans la population source. Les propriétés des estimateurs des effets d’exposition ont été étudiées par simulation. Différents aspects d’exposition ont été générés (intensité, durée, valeur cumulée d’exposition). Les données cas-témoins générées ont été ensuite analysées avec différentes versions du modèle de Cox, incluant les définitions anciennes et nouvelles des ensembles de sujets à risque, ainsi qu’avec la régression logistique conventionnelle, à des fins de comparaison. Les différents modèles de régression ont ensuite été appliqués sur des données réelles cas-témoins sur le cancer du poumon. Les estimations des effets de différentes variables de tabac, obtenues avec les différentes méthodes, ont été comparées entre elles, et comparées aux résultats des simulations. Résultats. Les résultats des simulations montrent que les estimations des nouveaux modèles de Cox pondérés proposés, surtout celles du Weighted Cox model, sont bien moins biaisées que les estimations des modèles de Cox existants qui incluent ou excluent simplement les futurs cas de chaque ensemble de sujets à risque. De plus, les estimations du Weighted Cox model étaient légèrement, mais systématiquement, moins biaisées que celles de la régression logistique. L’application aux données réelles montre de plus grandes différences entre les estimations de la régression logistique et des modèles de Cox pondérés, pour quelques variables de tabac dépendant du temps. Conclusions. Les résultats suggèrent que le nouveau modèle de Cox pondéré propose pourrait être une alternative intéressante au modèle de régression logistique, pour estimer les effets d’expositions dépendant du temps dans les études cas-témoins