69 resultados para methods: data analysis


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The present study focuses on single-case data analysis and specifically on two procedures for quantifying differences between baseline and treatment measurements The first technique tested is based on generalized least squares regression analysis and is compared to a proposed non-regression technique, which allows obtaining similar information. The comparison is carried out in the context of generated data representing a variety of patterns (i.e., independent measurements, different serial dependence underlying processes, constant or phase-specific autocorrelation and data variability, different types of trend, and slope and level change). The results suggest that the two techniques perform adequately for a wide range of conditions and researchers can use both of them with certain guarantees. The regression-based procedure offers more efficient estimates, whereas the proposed non-regression procedure is more sensitive to intervention effects. Considering current and previous findings, some tentative recommendations are offered to applied researchers in order to help choosing among the plurality of single-case data analysis techniques.

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The present paper advocates for the creation of a federated, hybrid database in the cloud, integrating law data from all available public sources in one single open access system - adding, in the process, relevant meta-data to the indexed documents, including the identification of social and semantic entities and the relationships between them, using linked open data techniques and standards such as RDF. Examples of potential benefits and applications of this approach are also provided, including, among others, experiences from of our previous research, in which data integration, graph databases and social and semantic networks analysis were used to identify power relations, litigation dynamics and cross-references patterns both intra and inter-institutionally, covering most of the World international economic courts.

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Fundamento: La prevalencia de discapacidad en la población general presenta una gran variabilidad geográfica, de manera que identificar aquellos factores que pudieran explicarla será importante para la planificación de políticas sociales. En este trabajo se analiza la variabilidad de la discapacidad por comunidades autónomas desde una doble vertiente, los factores individuales y del entorno. Métodos: Los datos proceden principalmente de la Encuesta de Discapacidad, Deficiencias y Estado de Salud de 1999 y del Inebase, ambas del Instituto Nacional de Estadística (INE). Se calculó la prevalencia de discapacidad simple y ajustada por edad de las CCAA. Se analizan los factores individuales asociados a la discapacidad mediante una regresión logística y los factores individuales y de la comunidad autónoma conjuntamente con una regresión logística de dos niveles. Resultados: La prevalencia de discapacidad muestra una diferencia máxima de 5,75 puntos entre las comunidades autónomas. En la regresión logística la comunidad de residencia fue estadísticamente significativa (OR: 3,35 en la de mayor prevalencia respecto a la de menor) junto con otras variables individuales: edad (OR de 40-64= 1,78 OR de 65-79= 1,87 y OR de >79= 3,34), sexo (OR mujer= 0,66), situación laboral (OR sin trabajo=2,25 OR amas casa/estudiante=1,39 y OR otros=2,03), estado de salud (OR regular= 1,69 OR malo/muy malo= 2,05) y enfermedades crónicas (OR 1-3=1,56 OR4-6=1,82 OR>6=2,59). En la regresión de dos niveles las variables individuales explican poca varianza (s=0,261) y ninguna de las variables relativas a las CCAA mejora el modelo. Conclusiones: Las características individuales no explican suficientemente la variabilidad de la discapacidad entre CCAA y no se han identificado variables del entorno que sean significativas.

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El presente trabajo tiene por objetivo principal analizar tres funciones de perfil del fuste sobre tres clones de Populus x euramericana (Canadá Blanco, I-214 y MC) en la Comunidad Foral de Navarra para elaborar una tarifa de cubicación con clasificación de volumen. Para minimizar el efecto de la autocorrelación entre los residuos se emplea una estructura de error continua autorregresiva de orden 2 o de orden 3 en función del clon analizado. Por otra parte, se compara el coeficiente local de forma de cada uno de los clones estudiados mediante dos metodologías: el análisis de la varianza de la estimación individual de dicho coeficiente y el contraste del estadístico de máxima verosimilitud entre ajustes, resultando ser el clon Canadá el más cónico de los tres. Los datos utilizados provienen de 143 chopos de plantaciones coetáneas y con mismo marco de plantación (marco real de 4,5 × 4,5 m).

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N = 1 designs imply repeated registrations of the behaviour of the same experimental unit and the measurements obtained are often few due to time limitations, while they are also likely to be sequentially dependent. The analytical techniques needed to enhance statistical and clinical decision making have to deal with these problems. Different procedures for analysing data from single-case AB designs are discussed, presenting their main features and revising the results reported by previous studies. Randomization tests represent one of the statistical methods that seemed to perform well in terms of controlling false alarm rates. In the experimental part of the study a new simulation approach is used to test the performance of randomization tests and the results suggest that the technique is not always robust against the violation of the independence assumption. Moreover, sensitivity proved to be generally unacceptably low for series lengths equal to 30 and 40. Considering the evidence available, there does not seem to be an optimal technique for single-case data analysis

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ABSTRACT Dual-trap optical tweezers are often used in high-resolution measurements in single-molecule biophysics. Such measurements can be hindered by the presence of extraneous noise sources, the most prominent of which is the coupling of fluctuations along different spatial directions, which may affect any optical tweezers setup. In this article, we analyze, both from the theoretical and the experimental points of view, the most common source for these couplings in dual-trap optical-tweezers setups: the misalignment of traps and tether. We give criteria to distinguish different kinds of misalignment, to estimate their quantitative relevance and to include them in the data analysis. The experimental data is obtained in a, to our knowledge, novel dual-trap optical-tweezers setup that directly measures forces. In the case in which misalignment is negligible, we provide a method to measure the stiffness of traps and tether based on variance analysis. This method can be seen as a calibration technique valid beyond the linear trap region. Our analysis is then employed to measure the persistence length of dsDNA tethers of three different lengths spanning two orders of magnitude. The effective persistence length of such tethers is shown to decrease with the contour length, in accordance with previous studies.

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The agricultural sector has always been characterized by a predominance of small firms. International competition and the consequent need for restraining costs are permanent challenges for farms. This paper performs an empirical investigation of cost behavior in agriculture using panel data analysis. Our results show that transactions caused by complexity influence farm costs with opposite effects for specific and indirect costs. While transactions allow economies of scale in specific costs, they significantly increase indirect costs. However, the main driver for farm costs is volume. In addition, important differences exist for small and big farms, since transactional variables significantly influence the former but not the latter. While sophisticated management tools, such ABC, could provide only limited complementary useful information but no essential allocation bases for farms, they seem inappropriate for small farms

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The agricultural sector has always been characterized by a predominance of small firms. International competition and the consequent need for restraining costs are permanent challenges for farms. This paper performs an empirical investigation of cost behavior in agriculture using panel data analysis. Our results show that transactions caused by complexity influence farm costs with opposite effects for specific and indirect costs. While transactions allow economies of scale in specific costs, they significantly increase indirect costs. However, the main driver for farm costs is volume. In addition, important differences exist for small and big farms, since transactional variables significantly influence the former but not the latter. While sophisticated management tools, such ABC, could provide only limited complementary useful information but no essential allocation bases for farms, they seem inappropriate for small farms

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The Erasmus Mundus Master in Quality in Analytical Laboratories (EMQAL) is a two-year Joint Master Degree. The course is funded by the European Commission through the Erasmus Mundus Programme, providing a number of attractive scholarships for European and non-European students. EMQAL prepares professionals for analytical laboratories, focusing on laboratory management and quality systems, along with complementing their technical knowledge. The EMQAL aims at training students in the most relevant issues concerning quality systems and management in analytical laboratories, and to become an expert in: Quality management, Analytical methods and Data Analysis. EMQAL promotes mobility. The students will attend one academic year of lectures in one of the European universities of the EMQAL consortium, and a 12 months master thesis at other European university, with the possibility to spend three-months in one of the non-EU partners. The language of instruction and examination is English. Further information is available at www.emqal.org.