4 resultados para Generalized Likelihood Ratio

em Universidade Federal do Rio Grande do Norte(UFRN)


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Urinary incontinence (UI) is a geriatric syndrome that is especially prevalent in institutionalized individuals, and that causes economic and social impacts derived from treatment costs and overload of caregiver. UI also entails physical consequences to the health of the elderly, such as urinary tract infections or pressure ulcers, among other health problems. However, the existing national research on this condition is still scarce and comprises serious methodological biases. Therefore, the objective of this study is to determine the prevalence of urinary incontinence and associated factors in institutionalized elderly. A cross-sectional study is presented herein, conducted between October and December, 2013 and carried out in 10 nursing homes in the city of Natal (Northeast Brazil). UI was verified through the program Minimum Data Set version 3.0, which was also used to assess fecal incontinence, urinary devices and UI control programs. Data collection included sociodemographic information, UI characterization, as well as variables related to the institution itself and to health conditions (comorbidities, medication, pelvic floor surgery, Barthel Index for functional capacity and Pfeiffer test for cognitive status). Bivariate analysis was performed using the Chi-Square Test (or Fisher‟s Exact Test) and the Linear Chi-Square Test, calculating the prevalence ratio with 95% confidence interval. Variables with p value under 0.20 were included in the multivariate analysis, which was performed using the Stepwise Forward logistic regression. The inclusion of variables in the final model depended on the likelihood ratio test, absence of multicollinearity and on the Hosmer-Lemeshow test. A statistical significance level of 0.05 was considered. Six (1.8%) hospitalized elderly, one individual in palliative care (0.3%) and one (0.3%) individual under the age of 60 were excluded from the study. The final sample consisted of 321 elderly, mostly females, with a mean age of 81.5 years. The prevalence of UI was 59.43% and the final model revealed statistically a significant association between UI and white race, physical inactivity, stroke, mobility constraints and cognitive decline. The most frequent UI type was functional UI due to physical or cognitive disability, and incontinence control measures were applied only to a minority of residents (approximately 8%). It is concluded that UI is a health issue that affects more than half of the institutionalized elderly, and is associated with white race, physical inactivity, stroke and other geriatric syndromes such as immobility and cognitive disability. Most of these associated factors are modifiable and therefore the findings of this study highlight the importance of UI prevention and treatment in nursing homes, which include general measures, such as physical and psychosocial activities, and specific measures, such as prompted voiding

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In survival analysis, the response is usually the time until the occurrence of an event of interest, called failure time. The main characteristic of survival data is the presence of censoring which is a partial observation of response. Associated with this information, some models occupy an important position by properly fit several practical situations, among which we can mention the Weibull model. Marshall-Olkin extended form distributions other a basic generalization that enables greater exibility in adjusting lifetime data. This paper presents a simulation study that compares the gradient test and the likelihood ratio test using the Marshall-Olkin extended form Weibull distribution. As a result, there is only a small advantage for the likelihood ratio test

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Survival models deals with the modeling of time to event data. However in some situations part of the population may be no longer subject to the event. Models that take this fact into account are called cure rate models. There are few studies about hypothesis tests in cure rate models. Recently a new test statistic, the gradient statistic, has been proposed. It shares the same asymptotic properties with the classic large sample tests, the likelihood ratio, score and Wald tests. Some simulation studies have been carried out to explore the behavior of the gradient statistic in fi nite samples and compare it with the classic statistics in diff erent models. The main objective of this work is to study and compare the performance of gradient test and likelihood ratio test in cure rate models. We first describe the models and present the main asymptotic properties of the tests. We perform a simulation study based on the promotion time model with Weibull distribution to assess the performance of the tests in finite samples. An application is presented to illustrate the studied concepts

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Survival models deals with the modelling of time to event data. In certain situations, a share of the population can no longer be subjected to the event occurrence. In this context, the cure fraction models emerged. Among the models that incorporate a fraction of cured one of the most known is the promotion time model. In the present study we discuss hypothesis testing in the promotion time model with Weibull distribution for the failure times of susceptible individuals. Hypothesis testing in this model may be performed based on likelihood ratio, gradient, score or Wald statistics. The critical values are obtained from asymptotic approximations, which may result in size distortions in nite sample sizes. This study proposes bootstrap corrections to the aforementioned tests and Bartlett bootstrap to the likelihood ratio statistic in Weibull promotion time model. Using Monte Carlo simulations we compared the nite sample performances of the proposed corrections in contrast with the usual tests. The numerical evidence favors the proposed corrected tests. At the end of the work an empirical application is presented.