Motivational interviewing and feedback for college drinkers: Handling missing values with complete case analysis and multiple imputation

Objective: In this secondary data analysis, three statistical methodologies were implemented to handle cases with missing data in a motivational interviewing and feedback study. The aim was to evaluate the impact that these methodologies have on the data analysis. ^ Methods: We first evaluated whether the assumption of missing completely at random held for this study. We then proceeded to conduct a secondary data analysis using a mixed linear model to handle missing data with three methodologies (a) complete case analysis, (b) multiple imputation with explicit model containing outcome variables, time, and the interaction of time and treatment, and (c) multiple imputation with explicit model containing outcome variables, time, the interaction of time and treatment, and additional covariates (e.g., age, gender, smoke, years in school, marital status, housing, race/ethnicity, and if participants play on athletic team). Several comparisons were conducted including the following ones: 1) the motivation interviewing with feedback group (MIF) vs. the assessment only group (AO), the motivation interviewing group (MIO) vs. AO, and the intervention of the feedback only group (FBO) vs. AO, 2) MIF vs. FBO, and 3) MIF vs. MIO.^ Results: We first evaluated the patterns of missingness in this study, which indicated that about 13% of participants showed monotone missing patterns, and about 3.5% showed non-monotone missing patterns. Then we evaluated the assumption of missing completely at random by Little's missing completely at random (MCAR) test, in which the Chi-Square test statistic was 167.8 with 125 degrees of freedom, and its associated p-value was p=0.006, which indicated that the data could not be assumed to be missing completely at random. After that, we compared if the three different strategies reached the same results. For the comparison between MIF and AO as well as the comparison between MIF and FBO, only the multiple imputation with additional covariates by uncongenial and congenial models reached different results. For the comparison between MIF and MIO, all the methodologies for handling missing values obtained different results. ^ Discussions: The study indicated that, first, missingness was crucial in this study. Second, to understand the assumptions of the model was important since we could not identify if the data were missing at random or missing not at random. Therefore, future researches should focus on exploring more sensitivity analyses under missing not at random assumption.^

Effects of overweight and obesity on economic outcomes among U.S. adults with kidney disease

Background. Kidney disease is a growing public health phenomenon in the U.S. and in the world. Downstream interventions, dialysis and renal transplants covered by Medicare's renal disease entitlement policy in those who are 65 years and over have been expensive treatments that have been not foolproof. The shortage of kidney donors in the U.S. has grown in the last two decades. Therefore study of upstream events in kidney disease development and progression is justified to prevent the rising prevalence of kidney disease. Previous studies have documented the biological route by which obesity can progress and accelerate kidney disease, but health services literature on quantifying the effects of overweight and obesity on economic outcomes in the context of renal disease were lacking. Objectives . The specific aims of this study were (1) to determine the likelihood of overweight and obesity in renal disease and in three specific adult renal disease sub-populations, hypertensive, diabetic and both hypertensive and diabetic (2) to determine the incremental health service use and spending in overweight and obese renal disease populations and (3) to determine who financed the cost of healthcare for renal disease in overweight and obese adult populations less than 65 years of age. Methods. This study was a retrospective cross-sectional study of renal disease cases pooled for years 2002 to 2009 from the Medical Expenditure Panel Survey. The likelihood of overweight and obesity was estimated using chi-square test. Negative binomial regression and generalized gamma model with log link were used to estimate healthcare utilization and healthcare expenditures for six health event categories. Payments by self/family, public and private insurance were described for overweight and obese kidney disease sub-populations. Results. The likelihood of overweight and obesity was 0.29 and 0.46 among renal disease and obesity was common in hypertensive and diabetic renal disease population. Among obese renal disease population, negative binomial regression estimates of healthcare utilization per person per year as compared to normal weight renal disease persons were significant for office-based provider visits and agency home health visits respectively (p=0.001; p=0.005). Among overweight kidney disease population health service use was significant for inpatient hospital discharges (p=0.027). Over years 2002 to 2009, overweight and obese renal disease sub-populations had 53% and 63% higher inpatient facility and doctor expenditures as compared to normal weight renal disease population and these result were statistically significant (p=0.007; p=0.026). Overweigh renal disease population had significant total expenses per person per year for office-based and outpatient associated care. Overweight and obese renal disease persons paid less from out-of-pocket overall compared to normal weight renal disease population. Medicare and Medicaid had the highest mean annual payments for obese renal disease persons, while mean annual payments per year were highest for private insurance among normal weight renal disease population. Conclusion. Overweight and obesity were common in those with acute and chronic kidney disease and resulted in higher healthcare spending and increased utilization of office-based providers, hospital inpatient department and agency home healthcare. Healthcare for overweight and obese renal disease persons younger than 65 years of age was financed more by private and public insurance and less by out of pocket payments. With the increasing epidemic of obesity in the U.S. and the aging of the baby boomer population, the findings of the present study have implications for public health and for greater dissemination of healthcare resources to prevent, manage and delay the onset of overweight and obesity that can progress and accelerate the course of the kidney disease.^

Identification of genes associated with quantitative traits involved in cardiovascular disease and lipoprotein metabolism

Cardiovascular disease (CVD) is a threat to public health. It has been reported to be the leading cause of death in United States. The invention of next generation sequencing (NGS) technology has revolutionized the biomedical research. To investigate NGS data of CVD related quantitative traits would contribute to address the unknown etiology and disease mechanism of CVD. NHLBI's Exome Sequencing Project (ESP) contains CVD related phenotypes and their associated NGS exomes sequence data. Initially, a subset of next generation sequencing data consisting of 13 CVD-related quantitative traits was investigated. Only 6 traits, systolic blood pressure (SBP), diastolic blood pressure (DBP), height, platelet counts, waist circumference, and weight, were analyzed by functional linear model (FLM) and 7 currently existing methods. FLM outperformed all currently existing methods by identifying the highest number of significant genes and had identified 96, 139, 756, 1162, 1106, and 298 genes associated with SBP, DBP, Height, Platelet, Waist, and Weight respectively. ^

New methods for quantification and analysis of quantitative real-time polymerase chain reaction data

Quantitative real-time polymerase chain reaction (qPCR) is a sensitive gene quantitation method that has been widely used in the biological and biomedical fields. The currently used methods for PCR data analysis, including the threshold cycle (CT) method, linear and non-linear model fitting methods, all require subtracting background fluorescence. However, the removal of background fluorescence is usually inaccurate, and therefore can distort results. Here, we propose a new method, the taking-difference linear regression method, to overcome this limitation. Briefly, for each two consecutive PCR cycles, we subtracted the fluorescence in the former cycle from that in the later cycle, transforming the n cycle raw data into n-1 cycle data. Then linear regression was applied to the natural logarithm of the transformed data. Finally, amplification efficiencies and the initial DNA molecular numbers were calculated for each PCR run. To evaluate this new method, we compared it in terms of accuracy and precision with the original linear regression method with three background corrections, being the mean of cycles 1-3, the mean of cycles 3-7, and the minimum. Three criteria, including threshold identification, max R2, and max slope, were employed to search for target data points. Considering that PCR data are time series data, we also applied linear mixed models. Collectively, when the threshold identification criterion was applied and when the linear mixed model was adopted, the taking-difference linear regression method was superior as it gave an accurate estimation of initial DNA amount and a reasonable estimation of PCR amplification efficiencies. When the criteria of max R2 and max slope were used, the original linear regression method gave an accurate estimation of initial DNA amount. Overall, the taking-difference linear regression method avoids the error in subtracting an unknown background and thus it is theoretically more accurate and reliable. This method is easy to perform and the taking-difference strategy can be extended to all current methods for qPCR data analysis.^

Snow-pit measurements on Atka Bay landfast sea ice during ANT-Land 2012/2013 season

Up to now, snow cover on Antarctic sea ice and its impact on radar backscatter, particularly after the onset of freeze/thaw processes, are not well understood. Here we present a combined analysis of in situ observations of snow properties from the landfast sea ice in Atka Bay, Antarctica, and high-resolution TerraSAR-X backscatter data, for the transition from austral spring (November 2012) to summer (January 2013). The physical changes in the seasonal snow cover during that time are reflected in the evolution of TerraSAR-X backscatter. We are able to explain 76-93% of the spatio-temporal variability of the TerraSAR-X backscatter signal with up to four snowpack parameters with a root-mean-squared error of 0.87-1.62 dB, using a simple multiple linear model. Over the complete study, and especially after the onset of early-melt processes and freeze/thaw cycles, the majority of variability in the backscatter is influenced by changes in snow/ice interface temperature, snow depth and top-layer grain size. This suggests it may be possible to retrieve snow physical properties over Antarctic sea ice from X-band SAR backscatter.

Strength and deformation behavior of ODP Leg 110 sediments

The shape and morphology of the northern Barbados Ridge complex is largely controlled by the sediment yield and failure behavior in response to high lateral loads imposed by convergence. Loads in excess of sediment yield strength result in nonrecoverable deformations within the wedge, and failure strength acts as an upper limit beyond which stresses are released through thrust faults. Relatively high loading rates lead to delayed consolidation and in-situ pore pressures greater than hydrostatic. The sediment yield and failure behavior is described for any stress path by a generalized constitutive model. A yield locus delineates the onset of plastic (non-recoverable) deformation, as defined from the isotropic and anisotropic consolidation responses of high-quality 38-mm triaxial specimens; a failure envelope was obtained by shearing the same specimens in both triaxial compression and extension. The yield locus is shown to be rotated into extension space and is centered about a K-line greater than unity, suggesting that the in-situ major principal stress has rotated into the horizontal plane, and that the sediment wedge is being subjected to extensional effective stress paths.

Whale sightings, group sizes and krill biomass in West Greenland in 2005

This study combined data on fin whale Balaenoptera physalus, humpback whale Megaptera novaeangliae, minke whale B. acutorostrata, and sei whale B. borealis sightings from large-scale visual aerial and ship-based surveys (248 and 157 sightings, respectively) with synoptic acoustic sampling of krill Meganyctiphanes norvegica and Thysanoessa sp. abundance in September 2005 in West Greenland to examine the relationships between whales and their prey. Krill densities were obtained by converting relationships of volume backscattering strengths at multiple frequencies to a numerical density using an estimate of krill target strength. Krill data were vertically integrated in 25 m depth bins between 0 and 300 m to obtain water column biomass (g/m**2) and translated to density surfaces using ordinary kriging. Standard regression models (Generalized Additive Modeling, GAM, and Generalized Linear Modeling, GLM) were developed to identify important explanatory variables relating the presence, absence, and density of large whales to the physical and biological environment and different survey platforms. Large baleen whales were concentrated in 3 focal areas: (1) the northern edge of Lille Hellefiske bank between 65 and 67°N, (2) north of Paamiut at 63°N, and (3) in South Greenland between 60 and 61° N. There was a bimodal pattern of mean krill density between depths, with one peak between 50 and 75 m (mean 0.75 g/m**2, SD 2.74) and another between 225 and 275 m (mean 1.2 to 1.3 g/m**2, SD 23 to 19). Water column krill biomass was 3 times higher in South Greenland than at any other site along the coast. Total depth-integrated krill biomass was 1.3 x 10**9 (CV 0.11). Models indicated the most important parameter in predicting large baleen whale presence was integrated krill abundance, although this relationship was only significant for sightings obtained on the ship survey. This suggests that a high degree of spatio-temporal synchrony in observations is necessary for quantifying predator-prey relationships. Krill biomass was most predictive of whale presence at depths >150 m, suggesting a threshold depth below which it is energetically optimal for baleen whales to forage on krill in West Greenland.

Responses of the tropical gorgonian coral Eunicea fusca to ocean acidification conditions

Ocean acidification can have negative repercussions from the organism to ecosystem levels. Octocorals deposit high-magnesium calcite in their skeletons, and according to different models, they could be more susceptible to the depletion of carbonate ions than either calcite or aragonite-depositing organisms. This study investigated the response of the gorgonian coral Eunicea fusca to a range of CO2 concentrations from 285 to 4,568 ppm (pH range 8.1-7.1) over a 4-week period. Gorgonian growth and calcification were measured at each level of CO2 as linear extension rate and percent change in buoyant weight and calcein incorporation in individual sclerites, respectively. There was a significant negative relationship for calcification and CO2 concentration that was well explained by a linear model regression analysis for both buoyant weight and calcein staining. In general, growth and calcification did not stop in any of the concentrations of pCO2; however, some of the octocoral fragments experienced negative calcification at undersaturated levels of calcium carbonate (>4,500 ppm) suggesting possible dissolution effects. These results highlight the susceptibility of the gorgonian coral E. fusca to elevated levels of carbon dioxide but suggest that E. fusca could still survive well in mid-term ocean acidification conditions expected by the end of this century, which provides important information on the effects of ocean acidification on the dynamics of coral reef communities. Gorgonian corals can be expected to diversify and thrive in the Atlantic-Eastern Pacific; as scleractinian corals decline, it is likely to expect a shift in these reef communities from scleractinian coral dominated to octocoral/soft coral dominated under a "business as usual" scenario of CO2 emissions.

Tendencias actuales en la construcción sismorresistente para edificios en hormigón armado

Este estudio aborda la recopilación de nuevas tendencias del diseño sismorresistente, enfocándose en la técnica del aislamiento de base, por ser la más efectiva, difundida y utilizada; y el análisis de las ventajas que puede tener una edificación que aplica dicha técnica, desde el punto de vista estructural y económico. Se elige la tipología más frecuente o común de edificios de hormigón armado propensos a ser aislados, que en este caso es un hospital, cuyo modelo empotrado se somete a varias normas sismorresistentes comparando principalmente fuerzas de cortante basal, y considerando la interacción suelo-estructura; para asistir a este cálculo se desarrolla un programa de elementos viga de 6 gdl por nodo en código Matlab. El modelo aislado incluye el análisis de tres combinaciones de tipos de aisladores HDR, LPR y FPS, alternando modelos lineales simplificados de 1 y 3 gdl por piso, evaluando diferencias de respuestas de la estructura, y procediendo a la elección de la combinación que de resultados más convenientes; para la modelación no lineal de cada sistema de aislamiento se utiliza el método explícito de diferencias centrales. Finalmente, se realiza un análisis comparativo de daños esperados en el caso de la ocurrencia del sismo de diseño, utilizando el método rápido y tomando como referencia el desplazamiento espectral del último piso; llegando a dar conclusiones y recomendaciones para el uso de sistemas de aislamiento. This study addresses the collection of new seismic design trends, focusing on base isolation technique, as the most effective and widely used, and the analysis of the advantages in buildings that apply this technique, from the structurally and economically point of view. Choosing the most common types of concrete buildings likely to be isolated, which in this case is a hospital, the fix model is subjected to various seismic codes mainly comparing base shear forces, and considering the soil-structure interaction; for this calculation attend a program of bars 6 dof per node is made in Matlab code. The isolated model includes analysis of three types of isolators combinations HDR, LPR and FPS, alternating simplified linear model of 1 and 3 dof per floor, evaluating differences in the response of the structure, and proceeding to the choice of the combination of results more convenient; for modeling nonlinear each insulation system, the explicit central difference method is used. Finally, a comparative analysis of expected damage in the case of the design earthquake, using a fast combined method and by reference to the spectral displacement of the top floor; reaching conclusions and give recommendations for the use of insulation systems.

Modelling the spatio-temporal pattern of primary dispersal in stone pine (Pinus pinea L.) stands in the Northern Plateau (Spain)

Natural regeneration in stone pine (Pinus pinea L.) managed forests in the Spanish Northern Plateau is not achieved successfully under current silviculture practices, constituting a main concern for forest managers. We modelled spatio-temporal features of primary dispersal to test whether (a) present low stand densities constrain natural regeneration success and (b) seed release is a climate-controlled process. The present study is based on data collected from a 6 years seed trap experiment considering different regeneration felling intensities. From a spatial perspective, we attempted alternate established kernels under different data distribution assumptions to fit a spatial model able to predict P. pinea seed rain. Due to P. pinea umbrella-like crown, models were adapted to account for crown effect through correction of distances between potential seed arrival locations and seed sources. In addition, individual tree fecundity was assessed independently from existing models, improving parameter estimation stability. Seed rain simulation enabled to calculate seed dispersal indexes for diverse silvicultural regeneration treatments. The selected spatial model of best fit (Weibull, Poisson assumption) predicted a highly clumped dispersal pattern that resulted in a proportion of gaps where no seed arrival is expected (dispersal limitation) between 0.25 and 0.30 for intermediate intensity regeneration fellings and over 0.50 for intense fellings. To describe the temporal pattern, the proportion of seeds released during monthly intervals was modelled as a function of climate variables – rainfall events – through a linear model that considered temporal autocorrelation, whereas cone opening took place over a temperature threshold. Our findings suggest the application of less intensive regeneration fellings, to be carried out after years of successful seedling establishment and, seasonally, subsequent to the main rainfall period (late fall). This schedule would avoid dispersal limitation and would allow for a complete seed release. These modifications in present silviculture practices would produce a more efficient seed shadow in managed stands.

Risk assessment of the spanish national railway system

The principal risks in the railway industry are mainly associated with collisions, derailments and level crossing accidents. An understanding of the nature of previous accidents on the railway network is required to identify potential causes and develop safety systems and deploy safety procedures. Risk assessment is a process for determining the risk magnitude to assist with decision-making. We propose a three-step methodology to predict the mean number of fatalities in railway accidents. The first is to predict the mean number of accidents by analyzing generalized linear models and selecting the one that best fits to the available historical data on the basis of goodness-offit statistics. The second is to compute the mean number of fatalities per accident and the third is to estimate the mean number of fatalities. The methodology is illustrated on the Spanish railway system. Statistical models accounting for annual and grouped data for the 1992-2009 time period have been analyzed. After identifying the models for broad and narrow gauges, we predicted mean number of accidents and the number of fatalities for the 2010-18 time period.

Estimation of daily global solar radiation from measured temperatures at Cañada de Luque, Córdoba, Argentina

Solar radiation is the most important source of renewable energy in the planet; it's important to solar engineers, designers and architects, and it's also fundamental for efficiently determining irrigation water needs and potential yield of crops, among others. Complete and accurate solar radiation data at a specific region are indispensable. For locations where measured values are not available, several models have been developed to estimate solar radiation. The objective of this paper was to calibrate, validate and compare five representative models to predict global solar radiation, adjusting the empirical coefficients to increase the local applicability and to develop a linear model. All models were based on easily available meteorological variables, without sunshine hours as input, and were used to estimate the daily solar radiation at Cañada de Luque (Córdoba, Argentina). As validation, measured and estimated solar radiation data were analyzed using several statistic coefficients. The results showed that all the analyzed models were robust and accurate (R2 and RMSE values between 0.87 to 0.89 and 2.05 to 2.14, respectively), so global radiation can be estimated properly with easily available meteorological variables when only temperature data are available. Hargreaves-Samani, Allen and Bristow-Campbell models could be used with typical values to estimate solar radiation while Samani and Almorox models should be applied with calibrated coefficients. Although a new linear model presented the smallest R2 value (R2 = 0.87), it could be considered useful for its easy application. The daily global solar radiation values produced for these models can be used to estimate missing daily values, when only temperature data are available, and in hydrologic or agricultural applications.

Regression analysis of top of descent location for idle-thrust descents

In this paper, multiple regression analysis is used to model the top of descent (TOD) location of user-preferred descent trajectories computed by the flight management system (FMS) on over 1000 commercial flights into Melbourne, Australia. In addition to recording TOD, the cruise altitude, final altitude, cruise Mach, descent speed, wind, and engine type were also identified for use as the independent variables in the regression analysis. Both first-order and second-order models are considered, where cross-validation, hypothesis testing, and additional analysis are used to compare models. This identifies the models that should give the smallest errors if used to predict TOD location for new data in the future. A model that is linear in TOD altitude, final altitude, descent speed, and wind gives an estimated standard deviation of 3.9 nmi for TOD location given the trajectory parame- ters, which means about 80% of predictions would have error less than 5 nmi in absolute value. This accuracy is better than demonstrated by other ground automation predictions using kinetic models. Furthermore, this approach would enable online learning of the model. Additional data or further knowledge of algorithms is necessary to conclude definitively that no second-order terms are appropriate. Possible applications of the linear model are described, including enabling arriving aircraft to fly optimized descents computed by the FMS even in congested airspace.

Tree and grazing influence on herbaceous pasture diversity in the Dehesa agroforestry system

Mediterranean Dehesas are one of the European natural habitat types of Community interest (43/92/EEC Directive), associated to high diversity levels and producer of important goods and services. In this work, tree contribution and grazing influence over pasture alpha diversity in a Dehesa in Central Spain was studied. We analyzed Richness and Shannon-Wiener (SW) indexes on herbaceous layer under 16 holms oak trees (64 sampling units distributed in two directions and in two distances to the trunk) distributed in four different grazing management zones (depending on species and stocking rate). Floristic composition by species or morphospecies and species abundance were analyzed for each sample unit. Linear mixed models (LMM) and generalized linear mixed models (GLMMs) were used to study relationships between alpha diversity measures and independent factors. Edge crown influence showed the highest values of Richness and SW index. No significant differences were found between orientations under tree crown influence. Grazing management had a significant effect over Richness and SW measures, specially the grazing species (cattle or sheep). We preliminary quantify and analyze the interaction of tree stratum and grazing management over herbaceous diversity in a year of extreme climatic conditions.

Percepciones sobre tres técnicas de evaluación de código: un estudio empírico sobre la intuición y las opiniones de los encargados de las pruebas de software

La Ingeniería del Software Empírico (ISE) utiliza como herramientas los estudios empíricos para conseguir evidencias que ayuden a conocer bajo qué circunstancias es mejor usar una tecnología software en lugar de otra. La investigación en la que se enmarca este TFM explora si las intuiciones y/o preferencias de las personas que realizan las pruebas de software, son capaces de predecir la efectividad de tres técnicas de evaluación de código: lectura por abstracciones sucesivas, cobertura de decisión y partición en clases de equivalencia. Para conseguir dicho objetivo, se analizan los datos recogidos en un estudio empírico, realizado por las tutoras de este TFM. En el estudio empírico distintos sujetos aplican las tres técnicas de evaluación de código a tres programas distintos, a los que se les habían introducido una serie de faltas artificialmente. Los sujetos deben reportar los fallos encontrados en los programas, así como, contestar a una serie de preguntas sobre sus intuiciones y preferencias. A la hora de analizar los datos del estudio, se ha comprobado: 1) cuáles son sus intuiciones y preferencias (mediante el test estadístico X2 de Pearson); 2) si los sujetos cambian de opinión después de aplicar las técnicas (para ello se ha utilizado índice de Kappa, el Test de McNemar-Bowker y el Test de Stuart-Maxwell); 3) la consistencia de las distintas preguntas (mediante el índice de Kappa), comparando: intuiciones con intuiciones, preferencias con preferencias e intuiciones con preferencias; 4) Por último, si hay coincidencia entre las intuiciones y preferencias con la efectividad real obtenida (para ello se ha utilizado, el Modelo Lineal General con medidas repetidas). Los resultados muestran que, no hay una intuición clara ni tampoco una preferencia concreta, con respecto a los programas. Además aunque existen cambios de opinión después de aplicar las técnicas, no se encuentran evidencias claras para afirmar que la intuición y preferencias influyen en su efectividad. Finalmente, existen relaciones entre las intuiciones con intuiciones, preferencias con preferencias e intuiciones con preferencias, además esta relación es más notoria después de aplicar las técnicas. ----ABSTRACT----Empirical Software Engineering (ESE) uses empirical studies as a mean to generate evidences to help determine under what circumstances it is convenient to use a given software technology. This Master Thesis is part of a research that explores whether intuitions and/or preferences of testers, can be used to predict the effectiveness of three code evaluation techniques: reading by stepwise abstractions, decision coverage and equivalence partitioning. To achieve this goal, this Master Thesis analyzes the data collected in an empirical study run by the tutors. In the empirical study, different subjects apply three code evaluation techniques to three different programs. A series of faults were artificially introduced to the programs. Subjects are required to report the defects found in the programs, as well as answer a series of questions about their intuitions and preferences. The data analyses test: 1) what are the intuitions and preferences of the subjects (using the Pearson X2 test); 2) whether subjects change their minds after applying the techniques (using the Kappa coefficient, McNemar-Bowker test, and Stuart-Maxwell test); 3) the consistency of the different questions, comparing: intuitions versus intuitions, preferences versus preferences and preferences versus intuitions (using the Kappa coefficient); 4) finally, if intuitions and/or preferences predict the actual effectiveness obtained (using the General Linear Model, repeated measures). The results show that there is not clear intuition or particular preference with respect to the programs. Moreover, although there are changes of mind after applying the techniques, there are not clear evidences to claim that intuition and preferences influence their effectiveness. Finally, there is a relationship between the intuitions versus intuitions, preferences versus preferences and intuitions versus preferences; this relationship is more noticeable after applying the techniques.