910 resultados para Negative Binomial Regression Model (NBRM)


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The objective of this study was to estimate (co)variance components using random regression on B-spline functions to weight records obtained from birth to adulthood. A total of 82 064 weight records of 8145 females obtained from the data bank of the Nellore Breeding Program (PMGRN/Nellore Brazil) which started in 1987, were used. The models included direct additive and maternal genetic effects and animal and maternal permanent environmental effects as random. Contemporary group and dam age at calving (linear and quadratic effect) were included as fixed effects, and orthogonal Legendre polynomials of age (cubic regression) were considered as random covariate. The random effects were modeled using B-spline functions considering linear, quadratic and cubic polynomials for each individual segment. Residual variances were grouped in five age classes. Direct additive genetic and animal permanent environmental effects were modeled using up to seven knots (six segments). A single segment with two knots at the end points of the curve was used for the estimation of maternal genetic and maternal permanent environmental effects. A total of 15 models were studied, with the number of parameters ranging from 17 to 81. The models that used B-splines were compared with multi-trait analyses with nine weight traits and to a random regression model that used orthogonal Legendre polynomials. A model fitting quadratic B-splines, with four knots or three segments for direct additive genetic effect and animal permanent environmental effect and two knots for maternal additive genetic effect and maternal permanent environmental effect, was the most appropriate and parsimonious model to describe the covariance structure of the data. Selection for higher weight, such as at young ages, should be performed taking into account an increase in mature cow weight. Particularly, this is important in most of Nellore beef cattle production systems, where the cow herd is maintained on range conditions. There is limited modification of the growth curve of Nellore cattle with respect to the aim of selecting them for rapid growth at young ages while maintaining constant adult weight.

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The recent advent of Next-generation sequencing technologies has revolutionized the way of analyzing the genome. This innovation allows to get deeper information at a lower cost and in less time, and provides data that are discrete measurements. One of the most important applications with these data is the differential analysis, that is investigating if one gene exhibit a different expression level in correspondence of two (or more) biological conditions (such as disease states, treatments received and so on). As for the statistical analysis, the final aim will be statistical testing and for modeling these data the Negative Binomial distribution is considered the most adequate one especially because it allows for "over dispersion". However, the estimation of the dispersion parameter is a very delicate issue because few information are usually available for estimating it. Many strategies have been proposed, but they often result in procedures based on plug-in estimates, and in this thesis we show that this discrepancy between the estimation and the testing framework can lead to uncontrolled first-type errors. We propose a mixture model that allows each gene to share information with other genes that exhibit similar variability. Afterwards, three consistent statistical tests are developed for differential expression analysis. We show that the proposed method improves the sensitivity of detecting differentially expressed genes with respect to the common procedures, since it is the best one in reaching the nominal value for the first-type error, while keeping elevate power. The method is finally illustrated on prostate cancer RNA-seq data.

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El minuto final de un partido ajustado de baloncesto es un momento crítico que está sujeto a multitud de factores que influyen en su desarrollo. Así, el porcentaje de acierto en los tiros libres durante ese periodo de tiempo va a determinar, en muchas ocasiones, el resultado final del partido. La disminución de rendimiento (drop) en esta faceta de juego en condiciones de presión, puede estar relacionada con múltiples variables propias del contexto deportivo estudiado, como por ejemplo: los segundos restantes de posesión, la situación en el marcador (ir ganando, empatando o perdiendo), la localización del partido (jugar en casa o fuera), la fase de competición (fase regular o eliminatorias) o el nivel del equipo (mejores/peores equipos). Además, las características del jugador que realiza los lanzamientos tienen una gran importancia respecto a su edad y años de experiencia para afrontar los momentos críticos, así como el puesto de juego que ocupa en el equipo. En este sentido, la combinación de factores del contexto y del jugador, permiten interactuar en el rendimiento del lanzador en los momentos finales de partido durante sus lanzamientos de tiro libre. El presente trabajo de tesis doctoral tiene como objetivo encontrar aquellas variables más relacionadas con la disminución de rendimiento del jugador en los tiros libres durante el último minuto de juego, y la última serie de tiros libres en los partidos ajustados de baloncesto. Para alcanzar el objetivo del estudio se analizaron 124 partidos ajustados (diferencias iguales o inferiores a 2 puntos) de todas las competiciones (fase regular, playoff y copa del Rey) de la liga ACB durante las temporadas 2011-2012 a 2014-2015. Para el registro de variables se analizó el porcentaje de acierto en los tiros libres del lanzador en la liga regular, partido completo, último minuto y última serie. De este modo se trató de analizar qué variables del contexto y del jugador permitían explicar el rendimiento en los tiros libres durante el último minuto, y la última serie de tiros libres del partido. Por otro lado, se trató de conocer el grado de asociación entre el descenso del rendimiento (drop) en los momentos finales de partido, y las variables estudiadas del jugador: puesto de juego, edad, y años de experiencia profesional; mientras que las variables situacionales consideradas fueron: fase de competición, localización, clasificación, tiempo restante, y diferencia parcial en el marcador. Para el análisis de los datos se realizaron dos modelos estadísticos: 1º) un modelo de regresión lineal múltiple para conocer el efecto de las variables independientes en el porcentaje de aciertos del lanzador en el último minuto, y en la última serie de tiros libres del partido; y 2º) un análisis de regresión logística binomial para analizar la relación existente entre la probabilidad de tener un drop (disminución del rendimiento) y las características del lanzador, y las variables situacionales. Los resultados del modelo de regresión lineal múltiple mostraron efectos negativos significativos en el porcentaje de acierto en los tiros libres durante el último minuto, cuando los lanzadores son los pívots (-19,45%). Por otro lado, los resultados durante la última serie mostraron el efecto negativo significativo sobre la posición de pívot (- 19,30%) y la diferencia parcial en el marcador (-3,33%, para cada punto de diferencia en el marcador) en el porcentaje de acierto en los tiros libres. Las variables independientes edad, experiencia profesional, clasificación en la liga regular, fase de competición, localización, y tiempo restante, no revelaron efectos significativos en los modelos de regresión lineal. Los resultados de la regresión logística binomial revelaron que las variables experiencia profesional entre 13 y 18 años (OR = 4,63), jugar de alero (OR = 23,01), y jugar de base (OR = 10,68) están relacionadas con una baja probabilidad de disminuir el rendimiento durante el último minuto del partido; mientras que ir ganando, aumenta esta probabilidad (OR = 0,06). Además, los resultados de la última serie mostraron una menor disminución del rendimiento del jugador cuando tiene entre 13 y 18 años de experiencia (OR = 4,28), y juega de alero (OR = 8,06) o base (OR = 6,34). Por el contrario, las variables situacionales relacionadas con esa disminución del rendimiento del jugador son las fases eliminatorias (OR = 0,22) e ir ganando (OR = 0,04). Los resultados principales del estudio mostraron que existe una disminución del rendimiento del jugador en su porcentaje de acierto en los tiros libres durante el último minuto y en la última serie de lanzamientos del partido, y que está relacionada significativamente con la edad, experiencia profesional, puesto de juego del jugador, y diferencia parcial en el marcador. Encontrando relación también con la fase de competición, durante la última serie de tiros libres del partido. Esta información supone una valiosa información para el entrenador, y su aplicación en el ámbito competitivo real. En este sentido, la creación de simulaciones en el apartado de aplicaciones prácticas, permite predecir el porcentaje de acierto en los tiros libres de un jugador durante los momentos de mayor presión del partido, en base a su perfil de rendimiento. Lo que puede servir para realizar una toma de decisiones más idónea, con el objetivo de lograr el mejor resultado. Del mismo modo, orienta el tipo de proceso de entrenamiento que se ha de seguir, en relación a los jugadores más tendentes al drop, con el objetivo de minimizar el efecto de la presión sobre su capacidad para rendir adecuadamente en la ejecución de los tiros libres, y lograr de esta manera un rendimiento más homogéneo en todos los jugadores del equipo en esta faceta del juego, durante el momento crítico del final de partido. ABSTRACT. The final minute of a close game in basketball is a critical moment which is subject to many factors that influence its development. Thus, the success rate in free-throws during that period will determine, in many cases, the outcome of the game. Decrease of performance (drop) in this facet of play under pressure conditions, may be related to studied own multiple sports context variables, such as the remaining seconds of possession, the situation in the score (to be winning, drawing, or losing) the location of the match (playing at home or away), the competition phase (regular season or playoffs) or team level (best/worst teams). In addition, the characteristics of the player are very important related to his age and years of experience to face the critical moments, as well as his playing position into team. In this sense, the combination of factors in context and player, allows interact about performance of shooter in the final moments of the game during his free-throw shooting. The aim of this present doctoral thesis was find the most related variables to player´s drop in free throws in the last minute of the game and the last row of free-throws in closed games of basketball. To achieve the objective of the study, 124 closed games (less or equal than 2 points difference) were analyzed in every copetition in ACB league (regular season, playoff and cup) from 2011-2012 to 2014-2015 seasons. To record the variables, the percentage of success of the shooter in regular season, full game, last minute, and last row were analyzed. This way, it is tried to analyze which player and context variables explain the free-throw performance in last minute and last row of the game. On the other hand, it is tried to determine the degree of association between decrease of performance (drop) of the player in the final moments, and studied player variables: playing position, age, and years of professional experience; while considered situational variables considered were: competition phase, location, classification, remaining time, and score-line. For data analysis were performed two statistical models: 1) A multiple linear regression model to determine the effect of the independent variables in the succsess percentage of shooter at the last minute, and in the last row of free-throws in the game; and 2) A binomial logistic regression analysis to analyze the relationship between the probability of a drop (lower performance) and the characteristics of the shooter and situational variables. The results of multiple linear regression model showed significant negative effects on the free-throw percentage during last minute, when shooters are centers (-19.45%). On the other hand, results in the last series showed the significant negative effect on the center position (-19.30%) and score-line (-3.33% for each point difference in the score) in the free-throw percentage. The independent variables age, professional experience, ranking in the regular season, competition phase, location, and remaining time, revealed no significant effects on linear regression models. The results of the binomial logistic regression showed that the variables professional experience between 13 and 18 years (OR = 4.63), playing forward (OR = 23.01) and playing guard (OR = 10.68) are related to reduce the probability to decrease the performance during the last minute of the game. While wining, increases it (OR = 0.06). Furthermore, the results of the last row showed a reduction in performance degradation when player is between 13 and 18 years of experience (OR = 4.28), and playing forward (OR = 8.06) or guard (OR = 6.34). By contrast, the variables related to the decrease in performance of the player are the knockout phases (OR = 0.22) and wining (OR = 0.04). The main results of the study showed that there is a decrease in performance of the player in the percentage of success in free-throws in the last minute and last row of the game, and it is significantly associated with age, professional experience, and player position. Finding relationship with the competition phase, during last row of free-throws of the game too. This information is a valuable information for the coach, for applying in real competitive environment. In this sense, create simulations in the section of practical applications allows to predict the success rate of free-throw of a player during the most pressing moments of the game, based on their performance profile. What can be used to take more appropriate decisions in order to achieve the best result. Similarly, guides the type of training process must be followed in relation to the most favorable players to drop, in order to minimize the effect of pressure on their ability to perform properly in the execution of the free-throws. And to achieve, in this way, a more consistent performance in all team players in this facet of the game, during the critical moment in the final of the game.

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La duración del viaje vacacional es una decisión del turista con unas implicaciones fundamentales para las organizaciones turísticas, pero que ha recibido una escasa atención por la literatura. Además, los escasos estudios se han centrado en los destinos costeros, cuando el turismo de interior se está erigiendo como una alternativa importante en algunos países. El presente trabajo analiza los factores determinantes de la elección temporal del viaje turístico, distinguiendo el tipo de destino elegido -costa e interior-, y proponiendo varias hipótesis acerca de la influencia de las características de los individuos relacionadas con el destino, de las restricciones personales y de las características sociodemográficas. La metodología aplicada estima, como novedad en este tipo de decisiones, un Modelo Binomial Negativo Truncado que evita los sesgos de estimación de los modelos de regresión y el supuesto restrictivo de igualdad media-varianza del Modelo de Poisson. La aplicación empírica realizada en España sobre una muestra de 1.600 individuos permite concluir, por un lado, que el Modelo Binomial Negativo es más adecuado que el de Poisson para realizar este tipo de análisis. Por otro lado, las dimensiones determinantes de la duración del viaje vacacional son, para ambos destinos, el alojamiento en hotel y apartamento propio, las restricciones temporales, la edad del turista y la forma de organizar el viaje; mientras que el tamaño de la ciudad de residencia y el atributo “precios baratos” es un aspecto diferencial de la costa; y el alojamiento en apartamentos alquilados lo es de los destinos de interior.

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The use of presence/absence data in wildlife management and biological surveys is widespread. There is a growing interest in quantifying the sources of error associated with these data. We show that false-negative errors (failure to record a species when in fact it is present) can have a significant impact on statistical estimation of habitat models using simulated data. Then we introduce an extension of logistic modeling, the zero-inflated binomial (ZIB) model that permits the estimation of the rate of false-negative errors and the correction of estimates of the probability of occurrence for false-negative errors by using repeated. visits to the same site. Our simulations show that even relatively low rates of false negatives bias statistical estimates of habitat effects. The method with three repeated visits eliminates the bias, but estimates are relatively imprecise. Six repeated visits improve precision of estimates to levels comparable to that achieved with conventional statistics in the absence of false-negative errors In general, when error rates are less than or equal to50% greater efficiency is gained by adding more sites, whereas when error rates are >50% it is better to increase the number of repeated visits. We highlight the flexibility of the method with three case studies, clearly demonstrating the effect of false-negative errors for a range of commonly used survey methods.

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Run-off-road (ROR) crashes have increasingly become a serious concern for transportation officials in the State of Florida. These types of crashes have increased proportionally in recent years statewide and have been the focus of the Florida Department of Transportation. The goal of this research was to develop statistical models that can be used to investigate the possible causal relationships between roadway geometric features and ROR crashes on Florida's rural and urban principal arterials. ^ In this research, Zero-Inflated Poisson (ZIP) and Zero-Inflated Negative Binomial (ZINB) Regression models were used to better model the excessive number of roadway segments with no ROR crashes. Since Florida covers a diverse area and since there are sixty-seven counties, it was divided into four geographical regions to minimize possible unobserved heterogeneity. Three years of crash data (2000–2002) encompassing those for principal arterials on the Florida State Highway System were used. Several statistical models based on the ZIP and ZINB regression methods were fitted to predict the expected number of ROR crashes on urban and rural roads for each region. Each region was further divided into urban and rural areas, resulting in a total of eight crash models. A best-fit predictive model was identified for each of these eight models in terms of AIC values. The ZINB regression was found to be appropriate for seven of the eight models and the ZIP regression was found to be more appropriate for the remaining model. To achieve model convergence, some explanatory variables that were not statistically significant were included. Therefore, strong conclusions cannot be derived from some of these models. ^ Given the complex nature of crashes, recommendations for additional research are made. The interaction of weather and human condition would be quite valuable in discerning additional causal relationships for these types of crashes. Additionally, roadside data should be considered and incorporated into future research of ROR crashes. ^

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The relationship between workplace absenteeism and adverse lifestyle factors (smoking, physical inactivity and poor dietary patterns) remains ambiguous. Reliance on self-reported absenteeism and obesity measures may contribute to this uncertainty. Using objective absenteeism and health status measures, the present study aimed to investigate what health status outcomes and lifestyle factors influence workplace absenteeism. Cross-sectional data were obtained from a complex workplace dietary intervention trial, the Food Choice at Work Study. Four multinational manufacturing workplaces in Cork, Republic of Ireland. Participants included 540 randomly selected employees from the four workplaces. Annual count absenteeism data were collected. Physical assessments included objective health status measures (BMI, midway waist circumference and blood pressure). FFQ measured diet quality from which DASH (Dietary Approaches to Stop Hypertension) scores were constructed. A zero-inflated negative binomial (zinb) regression model examined associations between health status outcomes, lifestyle characteristics and absenteeism. The mean number of absences was 2·5 (sd 4·5) d. After controlling for sociodemographic and lifestyle characteristics, the zinb model indicated that absenteeism was positively associated with central obesity, increasing expected absence rate by 72 %. Consuming a high-quality diet and engaging in moderate levels of physical activity were negatively associated with absenteeism and reduced expected frequency by 50 % and 36 %, respectively. Being in a managerial/supervisory position also reduced expected frequency by 50 %. To reduce absenteeism, workplace health promotion policies should incorporate recommendations designed to prevent and manage excess weight, improve diet quality and increase physical activity levels of employees.

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Assessing the fit of a model is an important final step in any statistical analysis, but this is not straightforward when complex discrete response models are used. Cross validation and posterior predictions have been suggested as methods to aid model criticism. In this paper a comparison is made between four methods of model predictive assessment in the context of a three level logistic regression model for clinical mastitis in dairy cattle; cross validation, a prediction using the full posterior predictive distribution and two “mixed” predictive methods that incorporate higher level random effects simulated from the underlying model distribution. Cross validation is considered a gold standard method but is computationally intensive and thus a comparison is made between posterior predictive assessments and cross validation. The analyses revealed that mixed prediction methods produced results close to cross validation whilst the full posterior predictive assessment gave predictions that were over-optimistic (closer to the observed disease rates) compared with cross validation. A mixed prediction method that simulated random effects from both higher levels was best at identifying the outlying level two (farm-year) units of interest. It is concluded that this mixed prediction method, simulating random effects from both higher levels, is straightforward and may be of value in model criticism of multilevel logistic regression, a technique commonly used for animal health data with a hierarchical structure.

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BACKGROUND Despite great effort and investment incurred over decades to control bovine tuberculosis (bTB), it is still one of the most important zoonotic diseases in many areas of the world. Test-and-slaughter strategies, the basis of most bTB eradication programs carried out worldwide, have demonstrated its usefulness in the control of the disease. However, in certain countries, eradication has not been achieved due in part to limitations of currently available diagnostic tests. In this study, results of in-vivo and post-mortem diagnostic tests performed on 3,614 animals from 152 bTB-infected cattle herds (beef, dairy, and bullfighting) detected in 2007-2010 in the region of Castilla y León, Spain, were analyzed to identify factors associated with positive bacteriological results in cattle that were non-reactors to the single intradermal tuberculin test, to the interferon-gamma (IFN-γ) assay, or to both tests applied in parallel (Test negative/Culture + animals, T-/C+). The association of individual factors (age, productive type, and number of herd-tests performed since the disclosure of the outbreak) with the bacteriology outcome (positive/negative) was analyzed using a mixed multivariate logistic regression model. RESULTS The proportion of non-reactors with a positive post-mortem result ranged from 24.3% in the case of the SIT test to 12.9% (IFN-γ with 0.05 threshold) and 11.9% (95% CI 9.9-11.4%) using both tests in parallel. Older (>4.5 years) and bullfighting cattle were associated with increased odds of confirmed bTB infection by bacteriology, whereas dairy cattle showed a significantly lower risk. Ancillary use of IFN-γ assay reduced the proportion of T-/C + animals in high risk groups. CONCLUSIONS These results demonstrate the likelihood of positive bacteriological results in non-reactor cattle is influenced by individual epidemiological factors of tested animals. Increased surveillance on non-reactors with an increased probability of being false negative could be helpful to avoid bTB persistence, particularly in chronically infected herds. These findings may aid in the development of effective strategies for eradication of bTB in Spain.

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Objective: Wives of pathological gamblers tend to endure long marriages despite financial and emotional burden. Difficulties in social adjustment, personality psychopathology, and comorbidity with psychiatric disorders are pointed as reasons for remaining on such overwhelming relationships. The goal was to examine the social adjustment, personality and negative emotionality of wives of pathological gamblers. Method: The sample consisted of 25 wives of pathological gamblers, mean age 40.6, SD = 9.1 from a Gambling Outpatient Unit and at GAM-ANON, and 25 wives of non-gamblers, mean age 40.8, SD = 9.1, who answered advertisements placed at the Universidade de São Paulo hospital and medical school complex. They were selected in order to approximately match demographic characteristics of the wives of pathological gamblers. Subjects were assessed by the Social Adjustment Scale, Temperament and Character Inventory, Beck Depression Inventory and State-Trait Anxiety Inventory. Results: Three variables remained in the final Multiple Logistic Regression model, wives of pathological gamblers presented greater dissatisfaction with their marital bond, and higher scores on Reward Dependence and Persistence temperament factors. Both, Wives of pathological gamblers and wives of non-gamblers presented well-structured character factors excluding personality disorders. Conclusion: This personality profile may explain wives of pathological gamblers emotional resilience and their marriage longevity. Co-dependence and other labels previously used to describe them may work as a double edged sword, legitimating wives of pathological gamblers problems, while stigmatizing them as inapt and needy.

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OBJETIVO: Estimar a prevalência de hipertensão arterial entre militares jovens e fatores associados. MÉTODOS: Estudo transversal realizado com amostra de 380 militares do sexo masculino de 19 e 35 anos de idade em uma unidade da Força Aérea Brasileira em São Paulo, SP, entre 2000 e 2001. Os pontos de corte para hipertensão foram: >140mmHg para pressão sistólica e > 90mmHg para pressão diastólica. As variáveis estudadas incluíram fatores de risco e de proteção para hipertensão, como características comportamentais e nutricionais. Para análise das associações, utilizou-se regressão linear generalizada múltipla, com família binomial e ligação logarítmica, obtendo-se razões de prevalências com intervalo de 90% de confiança e seleção hierarquizada das variáveis. RESULTADOS: A prevalência de hipertensão arterial foi de 22% (IC 90%: 21;29). No modelo final da regressão múltipla verificou-se prevalência de hipertensão 68% maior entre os ex-fumantes em relação aos não fumantes (IC 90%: 1,13;2,50). Entre os indivíduos com sobrepeso (índice de massa corporal - IMC de 25 a 29kg/m2) e com obesidade (IMC>29kg/m2) as prevalências foram, respectivamente, 75% (IC 90%: 1,23;2,50) e 178% (IC 90%: 1,82;4,25) maiores do que entre os eutróficos. Entre os que praticavam atividade física regular, comparado aos que não praticavam, a prevalência foi 52% menor (IC 90%: 0,30;0,90). CONCLUSÕES: Ser ex-fumante e ter sobrepeso ou obesidade foram situações de risco para hipertensão, enquanto que a prática regular de atividade física foi fator de proteção em militares jovens.

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This study aimed to describe and compare the ventilation behavior during an incremental test utilizing three mathematical models and to compare the feature of ventilation curve fitted by the best mathematical model between aerobically trained (TR) and untrained ( UT) men. Thirty five subjects underwent a treadmill test with 1 km.h(-1) increases every minute until exhaustion. Ventilation averages of 20 seconds were plotted against time and fitted by: bi-segmental regression model (2SRM); three-segmental regression model (3SRM); and growth exponential model (GEM). Residual sum of squares (RSS) and mean square error (MSE) were calculated for each model. The correlations between peak VO2 (VO2PEAK), peak speed (Speed(PEAK)), ventilatory threshold identified by the best model (VT2SRM) and the first derivative calculated for workloads below (moderate intensity) and above (heavy intensity) VT2SRM were calculated. The RSS and MSE for GEM were significantly higher (p < 0.01) than for 2SRM and 3SRM in pooled data and in UT, but no significant difference was observed among the mathematical models in TR. In the pooled data, the first derivative of moderate intensities showed significant negative correlations with VT2SRM (r = -0.58; p < 0.01) and Speed(PEAK) (r = -0.46; p < 0.05) while the first derivative of heavy intensities showed significant negative correlation with VT2SRM (r = -0.43; p < 0.05). In UT group the first derivative of moderate intensities showed significant negative correlations with VT2SRM (r = -0.65; p < 0.05) and Speed(PEAK) (r = -0.61; p < 0.05), while the first derivative of heavy intensities showed significant negative correlation with VT2SRM (r= -0.73; p < 0.01), Speed(PEAK) (r = -0.73; p < 0.01) and VO2PEAK (r = -0.61; p < 0.05) in TR group. The ventilation behavior during incremental treadmill test tends to show only one threshold. UT subjects showed a slower ventilation increase during moderate intensities while TR subjects showed a slower ventilation increase during heavy intensities.

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Purpose: The purpose of this study was to evaluate the effectiveness of combined ureteroscopic holmium YAG lithotripsy for renal calculi associated with ipsilateral ureteral stones. Materials and Methods: Between August 2002 and March 2007, retrograde flexible ureteroscopic stone treatment was attempted in 351 cases. Indication for treatment was concurrent symptomatic ureteral stones in 63 patients (group I). Additional operative time and perioperative complication rates were compared to a group of 39 patients submitted to ureteroscopic treatment for ureteral calculi exclusively (group II). Results: Mean ureteral stone size was 8.0 +/- 2.6 mm and 8.1 +/- 3.4 mm for groups I and II, respectively. Mean operative time for group I was 67.9 +/- 29.5 minutes and for group 2 was 49.3 +/- 13.2 minutes (p < 0.001). Flexible ureteroscopic therapy for renal calculi increased 18 minutes in the mean operative time. The overall complication rate was 3.1% and 2.5% for groups I and II, respectively (p = 0.87). Mean renal stone size was 10.7 +/- 6.4 mm, overall stone free rate in group I was 81%. However, considering only patients with renal stones smaller than 15 mm, the stone free rate was 88%. Successful treatment occurred in 81% of patients presenting lower pole stones, but only 76% of patients with multiple renal stones became stone free. As expected, stone free rate showed a significant negative correlation with renal stone size (p = 0.03; r = -0.36). Logistic regression model indicated an independent association of renal stones smaller than 15 mm and stone free rate (OR = 13.5; p = 0.01). Conclusion: Combined ureteroscopic treatment for ureteral and ipsilateral renal calculi is a safe and attractive option for patients presenting for symptomatic ureteral stone and ipsilateral renal calculi smaller than 15 mm.

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In this paper, we compare three residuals to assess departures from the error assumptions as well as to detect outlying observations in log-Burr XII regression models with censored observations. These residuals can also be used for the log-logistic regression model, which is a special case of the log-Burr XII regression model. For different parameter settings, sample sizes and censoring percentages, various simulation studies are performed and the empirical distribution of each residual is displayed and compared with the standard normal distribution. These studies suggest that the residual analysis usually performed in normal linear regression models can be straightforwardly extended to the modified martingale-type residual in log-Burr XII regression models with censored data.