3 resultados para Random sample

em Universitat de Girona, Spain


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El objetivo de este estudio es la evaluación de la ideación suicida infantil y su severidad a partir de la información proporcionada por el propio niño. Para ello se ha aplicado el Children’s Depression Inventory a una muestra representativa de 361 escolares de edades comprendidas entre los 8 y 12 años. Un mes más tarde se ha verificado la persistencia de los deseos de morir mediante la Children’s Depression Rating Scale-Revised. Se evalúa la severidad de la ideación suicida autoinformada con relación a la persistencia, la alteración del estado de ánimo y el conocimiento intelectual de la muerte. Los resultados indican que la persistencia de la intencionalidad suicida esta asociada a una mayor sintomatología depresiva

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Given an observed test statistic and its degrees of freedom, one may compute the observed P value with most statistical packages. It is unknown to what extent test statistics and P values are congruent in published medical papers. Methods: We checked the congruence of statistical results reported in all the papers of volumes 409–412 of Nature (2001) and a random sample of 63 results from volumes 322–323 of BMJ (2001). We also tested whether the frequencies of the last digit of a sample of 610 test statistics deviated from a uniform distribution (i.e., equally probable digits).Results: 11.6% (21 of 181) and 11.1% (7 of 63) of the statistical results published in Nature and BMJ respectively during 2001 were incongruent, probably mostly due to rounding, transcription, or type-setting errors. At least one such error appeared in 38% and 25% of the papers of Nature and BMJ, respectively. In 12% of the cases, the significance level might change one or more orders of magnitude. The frequencies of the last digit of statistics deviated from the uniform distribution and suggested digit preference in rounding and reporting.Conclusions: this incongruence of test statistics and P values is another example that statistical practice is generally poor, even in the most renowned scientific journals, and that quality of papers should be more controlled and valued

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One of the key aspects in 3D-image registration is the computation of the joint intensity histogram. We propose a new approach to compute this histogram using uniformly distributed random lines to sample stochastically the overlapping volume between two 3D-images. The intensity values are captured from the lines at evenly spaced positions, taking an initial random offset different for each line. This method provides us with an accurate, robust and fast mutual information-based registration. The interpolation effects are drastically reduced, due to the stochastic nature of the line generation, and the alignment process is also accelerated. The results obtained show a better performance of the introduced method than the classic computation of the joint histogram