578 resultados para 010402 Biostatistics


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In this study, the attitudes of students and teachers at the Faculty of Pharmaceutical Sciences of Araraquara (UNESP University) towards Biostatistics were assessed. The Survey of Attitudes Toward Statistics (SATS) scale was used as the measuring instrument. The reproducibility of the scale was estimated by Cohen's Kappa (κ) coefficient with linear weighting and its internal consistency by Cronbach's alpha coefficient (α). The individuals were first placed in two groups, according to their positive or negative attitude toward Statistics; then, the association of their attitude with the variables of interest was tested by the chi-squared (χ 2) test at a significance level of 5%. The sample consisted of 272 undergraduate students, 83 graduate students and 24 teachers, predominantly female (78.2%). Among the students, 67.5% participated in the scientific research initial training program. Reproducibility and internal consistency of the scale were adequate (κ=0.7093; α=0.9334). Most of the subjects (74.4%) had a positive attitude toward Statistics. Significant association was found between attitude and functional activity (p=0.0204), the course taken (p=0.0316) and effort (p=0.0002). Thus, it was concluded that the great majority of the participants had a positive attitude towards Biostatistics and that undergraduate students and those who reported good performance in Biostatistics showed a significantly higher proportion of positive attitude than the other students.

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Feathers are rich in amino acids and can be employed as a dietary protein supplement for animal feed. Microbial degradation is an alternative technology for improving the nutritional value of feathers. Other potential applications of keratinase include use in the leather industry, detergents and medicine as well as the pharmaceutical for the treatment of acne, psoriasis and calluses. A new keratinolytic enzyme production bacterium was isolated from a poultry processing plant. To improve keratinase yield, statistically based experimental designs were applied to optimize three significant variables: temperature, substrate concentration (feathers) and agitation speed. Response surface methodology demonstrated an increase in keratinolytic activity at temperature, agitation speed and substrate concentration of 26.6°C, 150 rpm and 2%, respectively. Liquid chromatography revealed the release of amino acids in the Bacillus amyloliquefaciens culture broth, thereby demonstrating the potential of feather meal in the animal feed industry. © Global Science Publications.

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Random regression models have been widely used to estimate genetic parameters that influence milk production in Bos taurus breeds, and more recently in B. indicus breeds. With the aim of finding appropriate random regression model to analyze milk yield, different parametric functions were compared, applied to 20,524 test-day milk yield records of 2816 first-lactation Guzerat (B. indicus) cows in Brazilian herds. The records were analyzed by random regression models whose random effects were additive genetic, permanent environmental and residual, and whose fixed effects were contemporary group, the covariable cow age at calving (linear and quadratic effects), and the herd lactation curve. The additive genetic and permanent environmental effects were modeled by the Wilmink function, a modified Wilmink function (with the second term divided by 100), a function that combined third-order Legendre polynomials with the last term of the Wilmink function, and the Ali and Schaeffer function. The residual variances were modeled by means of 1, 4, 6, or 10 heterogeneous classes, with the exception of the last term of the Wilmink function, for which there were 1, from 0.20 to 0.33. Genetic correlations between adjacent records were high values (0.83-0.99), but they declined when the interval between the test-day records increased, and were negative between the first and last records. The model employing the Ali and Schaeffer function with six residual variance classes was the most suitable for fitting the data. © FUNPEC-RP.

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A seleção de métodos apropriados para a análise estatística pode parecer complexa, principalmente para estudantes de pós-graduação e pesquisadores no início da carreira científica. Por outro lado, a apresentação em PowerPoint é uma ferramenta comum para estudantes e pesquisadores. Assim, um tutorial de Bioestatística desenvolvido em uma apresentação em PowerPoint poderia estreitar a distância entre ortodontistas e a Bioestatística. Esse guia proporciona informações úteis e objetivas a respeito de vários métodos estatísticos empregando exemplos relacionados à Odontologia e, mais especificamente, à Ortodontia. Esse tutorial deve ser empregado, principalmente, para o usuário obter algumas respostas a questões comuns relacionadas ao teste mais apropriado para executar comparações entre grupos, examinar correlações e regressões ou analisar o erro do método. Também pode ser obtido auxílio para checar a distribuição dos dados (normal ou anormal) e a escolha do gráfico mais adequado para a apresentação dos resultados. Esse guia pode ainda ser de bastante utilidade para revisores de periódicos examinarem, de forma rápida, a adequabilidade do método estatístico apresentado em um artigo submetido à publicação.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Background: The identification of useful quality indicators for nutrition therapy (QINTs) is of great interest and a challenge. This study attempted to identify the 10 QINTs that best suit the practice of quality control in nutrition therapy (NT) by evaluating the opinion of experts in NT with the use of psychometric techniques and statistical tools. Methods: Thirty-six QINTs available for clinical application in Brazil were assessed in 2 distinct phases. In phase 1, 26 nutrition experts ranked QINTs by scoring 4 attributes (utility, simplicity, objectivity, low cost) to assess each QINT on a 5-point Likert scale. The top 10 QINTs were identified from the 10 best scores obtained, and the reliability of expert opinion for each indicator was assessed by Cronbach's alpha. In phase 2, experts provided feedback regarding the selected top 10 QINTs by answering 2 closed questions. Results: The top 10 QINTs, in descending order, are the frequency of nutrition screening of hospitalized patients, diarrhea, involuntary withdrawal of enteral feeding tubes, feeding tube obstruction, fasting longer than 24 hours, glycemic dysfunction, estimated energy expenditure and protein needs, central venous catheter infection, compliance of NT indication, and frequency of application of subjective global assessment. Opinions were consistent among the interviewed experts. During feedback, 96% of experts were satisfied with the top 10 QINTs, and 100% had considered them in accordance with their previous opinion. Conclusion: The top 10 QINTs were identified according to their usefulness in clinical practice by obtaining adequate agreement and representativeness of opinion of nutrition experts. (Nutr Clin Pract. 2012;27:261-267)

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INTRODUCTION: The accurate evaluation of error of measurement (EM) is extremely important as in growth studies as in clinical research, since there are usually quantitatively small changes. In any study it is important to evaluate the EM to validate the results and, consequently, the conclusions. Because of its extreme simplicity, the Dahlberg formula is largely used worldwide, mainly in cephalometric studies. OBJECTIVES: (I) To elucidate the formula proposed by Dahlberg in 1940, evaluating it by comparison with linear regression analysis; (II) To propose a simple methodology to analyze the results, which provides statistical elements to assist researchers in obtaining a consistent evaluation of the EM. METHODS: We applied linear regression analysis, hypothesis tests on its parameters and a formula involving the standard deviation of error of measurement and the measured values. RESULTS AND CONCLUSION: we introduced an error coefficient, which is a proportion related to the scale of observed values. This provides new parameters to facilitate the evaluation of the impact of random errors in the research final results.

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Despite the widespread popularity of linear models for correlated outcomes (e.g. linear mixed modesl and time series models), distribution diagnostic methodology remains relatively underdeveloped in this context. In this paper we present an easy-to-implement approach that lends itself to graphical displays of model fit. Our approach involves multiplying the estimated marginal residual vector by the Cholesky decomposition of the inverse of the estimated marginal variance matrix. Linear functions or the resulting "rotated" residuals are used to construct an empirical cumulative distribution function (ECDF), whose stochastic limit is characterized. We describe a resampling technique that serves as a computationally efficient parametric bootstrap for generating representatives of the stochastic limit of the ECDF. Through functionals, such representatives are used to construct global tests for the hypothesis of normal margional errors. In addition, we demonstrate that the ECDF of the predicted random effects, as described by Lange and Ryan (1989), can be formulated as a special case of our approach. Thus, our method supports both omnibus and directed tests. Our method works well in a variety of circumstances, including models having independent units of sampling (clustered data) and models for which all observations are correlated (e.g., a single time series).