910 resultados para Negative Binomial Regression Model (NBRM)


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Perinteisesti ajoneuvojen markkinointikampanjoissa kohderyhmät muodostetaan yksinkertaisella kriteeristöllä koskien henkilön tai hänen ajoneuvonsa ominaisuuksia. Ennustavan analytiikan avulla voidaan tuottaa kohderyhmänmuodostukseen teknisesti kompleksisia mutta kuitenkin helppokäyttöisiä menetelmiä. Tässä työssä on sovellettu luokittelu- ja regressiomenetelmiä uuden auton ostajien joukkoon. Tämän työn menetelmiksi on rajattu tukivektorikone sekä Coxin regressiomalli. Coxin regression avulla on tutkittu elinaika-analyysien soveltuvuutta ostotapahtuman tapahtumahetken mallintamiseen. Luokittelu tukivektorikonetta käyttäen onnistuu tehtävässään noin 72% tapauksissa. Tukivektoriregressiolla mallinnetun hankintahetken virheen keskiarvo on noin neljä kuukautta. Työn tulosten perusteella myös elinaika-analyysin käyttö ostotapahtuman tapahtumahetken mallintamiseen on menetelmänä käyttökelpoinen.

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The aim of this master’s thesis is to analyze the effects of Foreign Direct Investments on growth in selected Central and Eastern European transition countries. The theoretical part of this thesis, introduces growth theories and how FDI is covered in those theories. In addition, the results from previous studies, which have studied FDI’s effect on growth, are presented in this master’s thesis. This work introduces also the economical progress during the transition period in selected countries. In the empirical part’s regression model, it will be searched for the direct effect of FDI on growth with panel data collected from nine transition countries.

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In Cerrado soils under grazing, changes occur in physical attributes, such as increased density, decreasing on the size of water stable aggregates, and macroporosity reduction. Thus, the aim of this study was to study the effect of compaction on the establishment of two forages. It was adopted a completely randomized design with three replications, in 2 x 4 factorial design, and two forages (Xaraés grass and Marandu grass), and four levels of compaction (soil densities of 1.0, 1.2, 1.4, and 1.6 Mg m-3). The following variables were evaluated 48 days after sowing: tiller population, plant height, dry matter production of shoots and components, leaf and stem, as well as the root dry mass. The stem dry mass decreased with soil density in a similar manner for both forages. It was observed that the leaf dry mass and shoots dry mass of Xaraés grass remained constant in the levels of soil compaction, not adjusting to any regression model. The establishment of Xaraés grass has not been negatively affected by compaction, which may be suitable for situations where there may be layers that restrict the growth of different forages.

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This experiment was conducted in Lavras - state of Minas Gerais (MG), Brazil, in a protected environment, and aims to estimate the irrigation depths that maximize productivity and economic returns in the cultivation of asparagus bean and analyze the economic viability of irrigation management. The experimental delineation was randomized blocks with five treatments and four replications. The treatments consisted of five drip irrigation depths: 40, 70, 100, 130 and 160% of water replacement depth up to field capacity. The depths of water that maximize productivity and economic returns were obtained from the regression model adjusted to productivity data, cost of product relations and water cost. The economic viability was achieved on the benefit/cost ratio basis. The depth with the maximum economic return was estimated in 434.4mm, with a productivity of 35,160.6kg ha-1, which is economically viable for the cultivation of asparagus bean, with a expected profitability of R$ 1.70 for every real invested.

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Some models have been developed using agrometeorological and remote sensing data to estimate agriculture production. However, it is expected that the use of SAR images can improve their performance. The main objective of this study was to estimate the sugarcane production using a multiple linear regression model which considers agronomic data and ALOS/PALSAR images obtained from 2007/08, 2008/09 and 2009/10 cropping seasons. The performance of models was evaluated by coefficient of determination, t-test, Willmott agreement index (d), random error and standard error. The model was able to explain 79%, 12% and 74% of the variation in the observed productions of the 2007/08, 2008/09 and 2009/10 cropping seasons, respectively. Performance of the model for the 2008/09 cropping season was poor because of the occurrence of a long period of drought in that season. When the three seasons were considered all together, the model explained 66% of the variation. Results showed that SAR-based yield prediction models can contribute and assist sugar mill technicians to improve such estimates.

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Objective: to assess predictors of intra-abdominal injuries in blunt trauma patients admitted without abdominal pain or abnormalities on the abdomen physical examination. Methods: We conducted a retrospective analysis of trauma registry data, including adult blunt trauma patients admitted from 2008 to 2010 who sustained no abdominal pain or abnormalities on physical examination of the abdomen at admission and were submitted to computed tomography of the abdomen and/or exploratory laparotomy. Patients were assigned into: Group 1 (with intra-abdominal injuries) or Group 2 (without intra-abdominal injuries). Variables were compared between groups to identify those significantly associated with the presence of intra-abdominal injuries, adopting p<0.05 as significant. Subsequently, the variables with p<0.20 on bivariate analysis were selected to create a logistic regression model using the forward stepwise method. Results: A total of 268 cases met the inclusion criteria. Patients in Group I were characterized as having significantly (p<0.05) lower mean AIS score for the head segment (1.0±1.4 vs. 1.8±1.9), as well as higher mean AIS thorax score (1.6±1.7 vs. 0.9±1.5) and ISS (25.7±14.5 vs. 17,1±13,1). The rate of abdominal injuries was significantly higher in run-over pedestrians (37.3%) and in motorcyclists (36.0%) (p<0.001). The resultant logistic regression model provided 73.5% accuracy for identifying abdominal injuries. The variables included were: motorcyclist accident as trauma mechanism (p<0.001 - OR 5.51; 95%CI 2.40-12.64), presence of rib fractures (p<0.003 - OR 3.00; 95%CI 1.47-6.14), run-over pedestrian as trauma mechanism (p=0.008 - OR 2.85; 95%CI 1.13-6.22) and abnormal neurological physical exam at admission (p=0.015 - OR 0.44; 95%CI 0.22-0.85). Conclusion Intra-abdominal injuries were predominantly associated with trauma mechanism and presence of chest injuries.

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The aim of this study was evaluate the risk factors for Mycobacterium avium subsp. paratuberculosis (Map) seroprevalence in sheep in the North of Portugal. The effects on seroprevalence of several variables such as individual characteristics, management practices, farm characteristics, animal health, and available veterinary services were evaluated. This information was then used in a multivariable logistic regression model in order to identify risk factors for Map seropositivity. Univariable analysis was used to screen the variables used in the logistic regression model. Variables that showed p values of <0.15 were retained for the multivariable analysis. Fifteen variables were associated with paratuberculosis in univariable analysis. The multivariable logistic regression model identified a number of variables as risk factors for seropositivity like sheep pure local and/or a cross of a local breed (OR=2.02), herd size with 31-60 head (OR=2.14), culling during the Spring-Summer season (OR=1.69) and the use of an anti-parasitic treatment such as Ivermectin as the only anti-parasitic medication (OR=5.60). Potential risk factors identified in this study support current recommendations for the control of paratuberculosis.

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This thesis examines the impact of foreign exchange rate volatility to the extent of use of foreign currency derivatives. Especially the focus is on the impacts of 2008 global financial crisis. The crisis increased risk level in the capital markets greatly. The change in the currency derivatives use is analyzed by comparing means between different periods and in addition, by linear regression that enables to analyze the explanatory power of the model. The research data consists of financial statements figures from fiscal years 2006-2011 published by firms operating in traditional Finnish industrial sectors. Volatilities of the chosen three currency pairs is calculated from the daily fixing rates of ECB. Based on the volatility the sample period is divided into three sub-periods. The results suggest that increased FX market volatility did not increase the use foreign currency derivatives. Furthermore, the increased foreign exchange rate volatility did not increase the power of linear regression model to estimate the use foreign currency derivatives compared to previous studies.

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Few data are available on the prevalence and risk factors of Chlamydophila abortus infection in goats in Brazil. A cross-sectional study was carried out to determine the flock-level prevalence of C. abortus infection in goats from the semiarid region of the Paraíba State, Northeast region of Brazil, as well as to identify risk factors associated with the infection. Flocks were randomly selected and a pre-established number of female goats > 12 mo old were sampled in each of these flocks. A total of 975 serum samples from 110 flocks were collected, and structured questionnaire focusing on risk factors for C. abortus infection was given to each farmer at the time of blood collection. For the serological diagnosis the complement fixation test (CFT) using C. abortus S26/3 strain as antigen was performed. The flock-level factors for C. abortus prevalence were tested using multivariate logistic regression model. Fifty-five flocks out of 110 presented at least one seropositive animal with an overall prevalence of 50.0% (95%; CI: 40.3%, 59.7%). Ninety-one out of 975 dairy goats examined were seropositive with titers >32, resulting in a frequency of 9.3%. Lend buck for breeding (odds ratio = 2.35; 95% CI: 1.04-5.33) and history of abortions (odds ratio = 3.06; 95% CI: 1.37-6.80) were associated with increased flock prevalence.

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Emex australis and E. spinosa are significant weed species in wheat and other crops. Information on the extent of competition of the Emex species will be helpful to access yield losses in wheat. Field experiments were conducted to quantify the interference of tested weed densities each as single or mixture of both at 1:1 on their growth and yield, wheat yield components and wheat grain yield losses in two consecutive years. Dry weight of both weed species increased from 3-6 g m-2 with every additional plant of weed, whereas seed number and weight per plant decreased with increasing density of either weed. Both weed species caused considerable decrease in yield components like spike bearing tillers, number of grains per spike, 1000-grain weight of wheat with increasing density population of the weeds. Based on non-linear hyperbolic regression model equation, maximum yield loss at asymptotic weed density was estimated to be 44 and 62% with E. australis, 56 and 70% with E. spinosa and 63 and 72% with mixture of both species at 1:1 during both year of study, respectively. It was concluded that E. spinosa has more competition effects on wheat crop as compared to E. australis.

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This master’s thesis studies the probability of bankruptcy of Finnish limited liability companies as a part of credit risk assessment. The main idea of this thesis is to build and test bankruptcy prediction models for Finnish limited liability companies that can be utilized in credit decision making. The data used in this thesis consists of historical financial statements from 2112 Finnish limited liability companies, half of which have filed for bankruptcy. A total of four models are developed, two with logistic regression and two with multivariate discriminant analysis (MDA). The time horizon of the models varies from 1 to 2 years prior to the bankruptcy, and 14 different financial variables are used in the model formation. The results show that the prediction accuracy of the models ranges between 81.7% and 88.9%, and the best prediction accuracy is achieved with the one year prior the bankruptcy logistic regression model. However the difference between the best logistic model and the best MDA model is minimal. Overall based on the results of this thesis it can be concluded that predicting bankruptcy is possible to some extent, but naturally the results are not perfect.

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We studied the ability of patients not experienced in the use of peak expiratory flow meters to assess the severity of their asthma exacerbations and compared it to the assessment of experienced clinicians. We also evaluated which data of physical examination and medical history are used by physicians to subjectively evaluate the severity of asthma attacks. Fifty-seven adult patients (15 men and 42 women, with a mean (± SD) age of 37.3 ± 14.5 years and 24.0 ± 17.9 years of asthma symptoms) with asthma exacerbations were evaluated in a University Hospital Emergency Department. Patients and physicians independently evaluated the severity of the asthma attack using a linear scale. Patient score, physician score and forced expiratory volume at the first second (FEV1) were correlated with history and physical examination variables, and were also considered as dependent variables in multiple linear regression models. FEV1 correlated significantly with the physician score (rho = 0.42, P = 0.001), but not with patient score (rho = 0.03; P = 0.77). Use of neck accessory muscles, expiratory time and wheezing intensity were the explanatory variables in the FEV1 regression model and were also present in the physician score model. We conclude that physicians evaluate asthma exacerbation severity better than patients and that physician's scoring of asthma severity correlated significantly with objective measures of airway obstruction (FEV1). Some variables (the use of neck accessory muscles, expiratory time and wheezing intensity) persisted as explanatory variables in physician score and FEV1 regression models, and should be emphasized in medical schools and emergency settings.

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The objective of the present study was to investigate clinical, echocardiographic and electrocardiographic (12-lead resting ECG, 24-h ambulatory ECG monitoring and signal-averaged ECG (SAECG)) parameters in subjects with chronic Chagas' disease in a long-term follow-up as prognostic markers for adverse outcomes. Fifty adult outpatients (34 to 74 years old, 31 females) staged according to Los Andes class I, II or III and complaining of palpitation were enrolled in a longitudinal study. SAECG was analyzed in time and frequency domains and the endpoint was a composite of cardiac death and ventricular tachycardia. During a follow-up of 84.2 ± 39.0 months, 34.0% of the patients developed adverse outcomes (9 cardiac deaths and 11 episodes of ventricular tachycardia). After optimal dichotomization, in a stepwise multivariate Cox-hazard regression model, apical aneurysm (HR = 3.7; 95% CI = 1.2-1.3; P = 0.02), left ventricular ejection fraction <62% (HR = 4.60; 95% CI = 1.39-15.24; P = 0.01) and incidence of ventricular premature contractions >614 per 24 h (hazard ratio = 6.1; 95% CI = 1.7-22.6; P = 0.006) were independent predictors of the composite endpoint. Although a high frequency content in SAECG demonstrated association with the presence of left ventricular dysfunction and myocardial fibrosis, its predictive value for the composite endpoint was not significant. Apical aneurysms, reduced left ventricular function and a high incidence of ventricular ectopic beats over a 24-h period have a strong predictive value for a composite endpoint of cardiac death and ventricular tachycardia in subjects with chronic Chagas' disease.

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Transitional cell carcinoma (TCC) of the urothelium is often multifocal and subsequent tumors may occur anywhere in the urinary tract after the treatment of a primary carcinoma. Patients initially presenting a bladder cancer are at significant risk of developing metachronous tumors in the upper urinary tract (UUT). We evaluated the prognostic factors of primary invasive bladder cancer that may predict a metachronous UUT TCC after radical cystectomy. The records of 476 patients who underwent radical cystectomy for primary invasive bladder TCC from 1989 to 2001 were reviewed retrospectively. The prognostic factors of UUT TCC were determined by multivariate analysis using the COX proportional hazards regression model. Kaplan-Meier analysis was also used to assess the variable incidence of UUT TCC according to different risk factors. Twenty-two patients (4.6%). developed metachronous UUT TCC. Multiplicity, prostatic urethral involvement by the bladder cancer and the associated carcinoma in situ (CIS) were significant and independent factors affecting the occurrence of metachronous UUT TCC (P = 0.0425, 0.0082, and 0.0006, respectively). These results were supported, to some extent, by analysis of the UUT TCC disease-free rate by the Kaplan-Meier method, whereby patients with prostatic urethral involvement or with associated CIS demonstrated a significantly lower metachronous UUT TCC disease-free rate than patients without prostatic urethral involvement or without associated CIS (log-rank test, P = 0.0116 and 0.0075, respectively). Multiple tumors, prostatic urethral involvement and associated CIS were risk factors for metachronous UUT TCC, a conclusion that may be useful for designing follow-up strategies for primary invasive bladder cancer after radical cystectomy.

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The objective of the present study was to investigate factors associated with cesarean sections in two cities located in different regions of Brazil and to determine factors that explain the higher cesarean section rate in the more developed city, Ribeirão Preto, compared to the less developed one, São Luís. Data from two cohort studies comprising 2846 women in Ribeirão Preto in 1994, and 2443 women in São Luís in 1997/1998 were used. Adjusted and non-adjusted risk estimates were calculated using a Poisson regression model. The cesarean section rate was 33.7% in São Luís and 50.8% in Ribeirão Preto. Adjusted analysis in a joint sequential model revealed a 51% higher risk of cesarean section in Ribeirão Preto compared to São Luís (prevalence rate ratio (PRR) = 1.51). Adjustment for category of hospital admission reduced the PRR to 1.09, i.e., this variable explained 82% of the difference in the cesarean section rate between the two cities. Adjustment for the variable "the same physician for prenatal care and delivery" reduced the PRR to 1.07, with the "physician" factor explaining 86% of the difference between rates. When simultaneously adjusted for the two variables, the PRR decreased to 1.05, with these two variables explaining 90% of the difference in the cesarean section rate between the two cities, and the difference was no longer significant. The difference in the cesarean section rate between the two Brazilian cities, one more and one less developed, was mainly explained by the physician factor and, to a lesser extent, by the category of hospital admission.