Time-series regression models to study the short-term effects of environmental factors on health

Time series regression models are especially suitable in epidemiology for evaluating short-term effects of time-varying exposures on health. The problem is that potential for confounding in time series regression is very high. Thus, it is important that trend and seasonality are properly accounted for. Our paper reviews the statistical models commonly used in time-series regression methods, specially allowing for serial correlation, make them potentially useful for selected epidemiological purposes. In particular, we discuss the use of time-series regression for counts using a wide range Generalised Linear Models as well as Generalised Additive Models. In addition, recently critical points in using statistical software for GAM were stressed, and reanalyses of time series data on air pollution and health were performed in order to update already published. Applications are offered through an example on the relationship between asthma emergency admissions and photochemical air pollutants

Coordinating Inventory Control and Pricing Strategies with Random Demand and Fixed Ordering Cost: The Finite Horizon Case

We analyze a finite horizon, single product, periodic review model in which pricing and production/inventory decisions are made simultaneously. Demands in different periods are random variables that are independent of each other and their distributions depend on the product price. Pricing and ordering decisions are made at the beginning of each period and all shortages are backlogged. Ordering cost includes both a fixed cost and a variable cost proportional to the amount ordered. The objective is to find an inventory policy and a pricing strategy maximizing expected profit over the finite horizon. We show that when the demand model is additive, the profit-to-go functions are k-concave and hence an (s,S,p) policy is optimal. In such a policy, the period inventory is managed based on the classical (s,S) policy and price is determined based on the inventory position at the beginning of each period. For more general demand functions, i.e., multiplicative plus additive functions, we demonstrate that the profit-to-go function is not necessarily k-concave and an (s,S,p) policy is not necessarily optimal. We introduce a new concept, the symmetric k-concave functions and apply it to provide a characterization of the optimal policy.

Markov chain montecarlo method applied to rounding zeros of compositional data: first approach

As stated in Aitchison (1986), a proper study of relative variation in a compositional data set should be based on logratios, and dealing with logratios excludes dealing with zeros. Nevertheless, it is clear that zero observations might be present in real data sets, either because the corresponding part is completely absent –essential zeros– or because it is below detection limit –rounded zeros. Because the second kind of zeros is usually understood as “a trace too small to measure”, it seems reasonable to replace them by a suitable small value, and this has been the traditional approach. As stated, e.g. by Tauber (1999) and by Martín-Fernández, Barceló-Vidal, and Pawlowsky-Glahn (2000), the principal problem in compositional data analysis is related to rounded zeros. One should be careful to use a replacement strategy that does not seriously distort the general structure of the data. In particular, the covariance structure of the involved parts –and thus the metric properties– should be preserved, as otherwise further analysis on subpopulations could be misleading. Following this point of view, a non-parametric imputation method is introduced in Martín-Fernández, Barceló-Vidal, and Pawlowsky-Glahn (2000). This method is analyzed in depth by Martín-Fernández, Barceló-Vidal, and Pawlowsky-Glahn (2003) where it is shown that the theoretical drawbacks of the additive zero replacement method proposed in Aitchison (1986) can be overcome using a new multiplicative approach on the non-zero parts of a composition. The new approach has reasonable properties from a compositional point of view. In particular, it is “natural” in the sense that it recovers the “true” composition if replacement values are identical to the missing values, and it is coherent with the basic operations on the simplex. This coherence implies that the covariance structure of subcompositions with no zeros is preserved. As a generalization of the multiplicative replacement, in the same paper a substitution method for missing values on compositional data sets is introduced

alr approach for replacing values below the detection limit

All of the imputation techniques usually applied for replacing values below the detection limit in compositional data sets have adverse effects on the variability. In this work we propose a modification of the EM algorithm that is applied using the additive log-ratio transformation. This new strategy is applied to a compositional data set and the results are compared with the usual imputation techniques

Multivariate ARIMA Compositional Time Series Analysis

A compositional time series is obtained when a compositional data vector is observed at different points in time. Inherently, then, a compositional time series is a multivariate time series with important constraints on the variables observed at any instance in time. Although this type of data frequently occurs in situations of real practical interest, a trawl through the statistical literature reveals that research in the field is very much in its infancy and that many theoretical and empirical issues still remain to be addressed. Any appropriate statistical methodology for the analysis of compositional time series must take into account the constraints which are not allowed for by the usual statistical techniques available for analysing multivariate time series. One general approach to analyzing compositional time series consists in the application of an initial transform to break the positive and unit sum constraints, followed by the analysis of the transformed time series using multivariate ARIMA models. In this paper we discuss the use of the additive log-ratio, centred log-ratio and isometric log-ratio transforms. We also present results from an empirical study designed to explore how the selection of the initial transform affects subsequent multivariate ARIMA modelling as well as the quality of the forecasts

Exercise sheet 2

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Exercise sheet 2 pdf

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Relación entre los estilos de liderazgo y los niveles de resiliencia de los subordinados

El presente documento hace un análisis de la influencia que ejercen los diferentes tipos de liderazgo, carismático y transaccional, de un directivo de una organización sobre los subordinados de la misma, que a su vez afecta positiva o negativamente el nivel de resiliencia de los mismos. De la misma forma, se ha identificado la relación que existe entre el nivel de resiliencia de los subordinados de una organización y el cumplimiento de objetivos corporativos de la misma. Todo lo anterior se justifica en la economía globalizada de la que ahora hacemos parte que obliga a las empresas a generar nuevas estrategias de competitividad dentro de ambientes turbulentos y cambiantes donde, el desarrollar y motivar el recurso humano de la organización toma importancia para la ejecución exitosa de estrategias diferenciales.

Análisis del gen adra2a receptor alfa 2a adrenergico en pacientes con trastorno de hiperactividad y déficit de atención

El trastorno de hiperactividad y déficit de atención (THDA), es definido clínicamente como una alteración en el comportamiento, caracterizada por inatención, hiperactividad e impulsividad. Estos aspectos son clasificados en tres subtipos, que son: Inatento, hiperactivo impulsivo y mixto. Clínicamente se describe un espectro amplio que incluye desordenes académicos, trastornos de aprendizaje, déficit cognitivo, trastornos de conducta, personalidad antisocial, pobres relaciones interpersonales y aumento de la ansiedad, que pueden continuar hasta la adultez. A nivel global se ha estimado una prevalencia entre el 1% y el 22%, con amplias variaciones, dadas por la edad, procedencia y características sociales. En Colombia, se han realizado estudios en Bogotá y Antioquia, que han permitido establecer una prevalencia del 5% y 15%, respectivamente. La causa específica no ha sido totalmente esclarecida, sin embargo se ha calculado una heredabilidad cercana al 80% en algunas poblaciones, demostrando el papel fundamental de la genética en la etiología de la enfermedad. Los factores genéticos involucrados se relacionan con cambios neuroquímicos de los sistemas dopaminérgicos, serotoninérgicos y noradrenérgicos, particularmente en los sistemas frontales subcorticales, corteza cerebral prefrontal, en las regiones ventral, medial, dorsolateral y la porción anterior del cíngulo. Basados en los datos de estudios previos que sugieren una herencia poligénica multifactorial, se han realizado esfuerzos continuos en la búsqueda de genes candidatos, a través de diferentes estrategias. Particularmente los receptores Alfa 2 adrenérgicos, se encuentran en la corteza cerebral, cumpliendo funciones de asociación, memoria y es el sitio de acción de fármacos utilizados comúnmente en el tratamiento de este trastorno, siendo esta la principal evidencia de la asociación de este receptor con el desarrollo del THDA. Hasta la fecha se han descrito más de 80 polimorfismos en el gen (ADRA2A), algunos de los cuales se han asociado con la entidad. Sin embargo, los resultados son controversiales y varían según la metodología diagnóstica empleada y la población estudiada, antecedentes y comorbilidades. Este trabajo pretende establecer si las variaciones en la secuencia codificante del gen ADRA2A, podrían relacionarse con el fenotipo del Trastorno de Hiperactividad y el Déficit de Atención.

Estudio de corte transversal en minería subterránea. Asociación entre los riesgos identificados por los trabajadores y los establecidos por las empresas. Boyacá - Colombia 2014.

Introducción. La minería subterránea de carbón en Colombia, es una de las áreas productivas más importantes con grandes oportunidades de trabajo para el capital obrero. Sin embargo en el sector se ha venido incrementando la accidentalidad problema que tiende a aumentar por el desarrollo proyectado para el 2019 en cuanto al número de trabajadores y la llegada de nuevas tecnologías. Objetivo. Determinar la asociación entre los riesgos identificados por los trabajadores y los establecidos por la empresa en los respectivos subprogramas de medicina preventiva y del trabajo, higiene y seguridad Industrial y caracterizar las actividades de los subprogramas de medicina preventiva y del trabajo, higiene y seguridad industrial implementados en las empresas. Materiales y métodos Se realizó un estudio de corte transversal, con el propósito de establecer frecuencias de asociación entre los riesgos identificados por los trabajadores y los establecidos por las empresas de minería subterránea de carbón en el departamento de Boyacá. Se aplicaron dos cuestionarios individual y de empresa, se hizo la caracterización de las actividades y se determino la asociación entre ambas por medio de análisis estadístico, la muestra fue probabilística, estratificada, con asignación proporcional aleatoria y por conglomerados bietapicos. Resultados El estudio evidenció que apenas se presenta un cumplimiento levemente superior al 50% del ordenamiento legal. En cuanto a la identificación y conocimiento del riesgo, la asociación entre el riesgo reconocido por los trabajadores y los reportados por la empresa fue significativo en físico ruido 16,2% y trabajo en caliente 8,88%. La asociación entre el uso de elementos de protección personal por parte de los trabajadores y los entregados por la empresa fue significativa en protección respiratoria con cartucho 75,80% y protección aditiva tipo inserción 78,00% y tipo copa 80,40%. Conclusiones Se encontró entre otros que los riesgos identificados por los trabajadores y establecidos por las empresas son muy pocos y que apenas se cumplen los requisitos legales vigentes.

Mediastinitis post revascularización miocárdica: impacto del cambio de profilaxis antibiótica en la fundación Cardioinfantil 2012 - 2013

INTRODUCCIÓN. La mediastinitis posterior a cirugía de revascularización miocárdica es una infección infrecuente, pero potencialmente fatal. En la Fundación Cardioinfantil se ha observado una tendencia al incremento de la misma en los últimos años, obligando a un cambio en las medidas de profilaxis antimicrobiana, pasando de cefalosporinas a vancomicina – gentamicina, sin embargo no se conoce aún el impacto de estas medidas. OBJETIVO: Determinar si el cambio de la profilaxis antibiótica en pacientes sometidos a revascularización miocárdica influye en una disminución de la incidencia de mediastinitis durante los años 2012 – 2013. METODOLOGÍA: Estudio de cohortes retrospectivo, evaluando la incidencia de mediastinitis post revascularización miocárdica, en pacientes expuestos a 2 diferentes tipos de profilaxis antimicrobiana (cefalosporinas vs vancomicina-gentamicina). Se describieron los patrones de susceptibilidad y resistencia de los patógenos encontrados en mediastinitis y la mortalidad de esta patología. RESULTADOS: Los patógenos más frecuentemente aislados en la mediastinitis fueron Staphylococcus aureus y Klebsiella pneumoniae, en la mayoría monomicrobiano. Se encontraron patógenos con perfiles de resistencia como betalactamasas de espectro extendido en Gram negativos y resistencia a la meticilina en cocos Gram positivos. El RR de mediastinitis del grupo expuesto a vancomicina-gentamicina respecto al grupo de cefalosporinas fue de 0,9 con IC 95% 0,28 – 3,28. CONCLUSIÓN: la epidemiologia microbiana de la mediastinitis no difiere de la reportada en otras series. La profilaxis antimicrobiana con vancomicina - gentamicina en pacientes sometidos a revascularización miocárdica, no redujo la incidencia de mediastinitis. Se propone regresar a la terapia de profilaxis con cefalosporinas.

Análisis bibliométrico de depresión infantil

El objetivo de este estudio fue identificar las tendencias en la investigación de la depresión infantil mediante un análisis bibliométrico de artículos publicados entre enero de 2010 y enero de 2015, en las bases de datos EBSCO, Scopus y Scielo. Se incluyeron 146 artículos, escritos en inglés, español y portugués. En el trabajo se identifican los autores más productivos y las tendencias de los autores con respecto al sexo, profesión y producción; así como los países, instituciones y revistas que más publicaron sobre dicho trastorno. La edad y la ansiedad son las variables que con más frecuencia se asocian al tema; de igual forma, se identificó el Children Depression Inventory (CDI) como el instrumento más común para medir la depresión infantil. En este periodo de tiempo destacan los artículos centrados en investigaciones sobre poblaciones con diferentes estados de salud, diseños correlacionales, de corte transversal y escritos por múltiples autores. Al analizar los resultados obtenidos se observa un creciente interés y preocupación de los investigadores por conocer la frecuencia de los trastornos del estado de ánimo y más específicamente de la depresión en niños, y la asociación e influencia que esta puede tener para su desarrollo.

Combined Analysis of the Short-Term Effects of Photochemical Air Pollutants on Mortality within the EMECAM Project

In recent years, some epidemiologic studies have attributed adverse effects of air pollutants on health not only to particles and sulfur dioxide but also to photochemical air pollutants (nitrogen dioxide and ozone). The effects are usually small, leading to some inconsistencies in the results of the studies. Furthermore, the different methodologic approaches of the studies used has made it difficult to derive generic conclusions. We provide here a quantitative summary of the short-term effects of photochemical air pollutants on mortality in seven Spanish cities involved in the EMECAM project, using generalized additive models from analyses of single and multiple pollutants. Nitrogen dioxide and ozone data were provided by seven EMECAM cities (Barcelona, Gijón, Huelva, Madrid, Oviedo, Seville, and Valencia). Mortality indicators included daily total mortality from all causes excluding external causes, daily cardiovascular mortality, and daily respiratory mortality. Individual estimates, obtained from city-specific generalized additive Poisson autoregressive models, were combined by means of fixed effects models and, if significant heterogeneity among local estimates was found, also by random effects models. Significant positive associations were found between daily mortality (all causes and cardiovascular) and NO2, once the rest of air pollutants were taken into account. A 10 μg/m3 increase in the 24-hr average 1-day NO2 level was associated with an increase in the daily number of deaths of 0.43% [95% confidence interval(CI), –0.003–0.86%] for all causes excluding external. In the case of significant relationships, relative risks for cause-specific mortality were nearly twice as much as that for total mortality for all the photochemical pollutants. Ozone was independently related only to cardiovascular daily mortality. No independent statistically significant relationship between photochemical air pollutants and respiratory mortality was found. The results in this study suggest that, given the present levels of photochemical pollutants, people living in Spanish cities are exposed to health risks derived from air pollution

Comparing meta-analysis and ecological-longitudinal analysis in time-series studies: a case study of the effects of air pollution on mortality in three Spanish cities

The objective of this paper is to introduce a diVerent approach, called the ecological-longitudinal, to carrying out pooled analysis in time series ecological studies. Because it gives a larger number of data points and, hence, increases the statistical power of the analysis, this approach, unlike conventional ones, allows the complementation of aspects such as accommodation of random effect models, of lags, of interaction between pollutants and between pollutants and meteorological variables, that are hardly implemented in conventional approaches. Design—The approach is illustrated by providing quantitative estimates of the short-termeVects of air pollution on mortality in three Spanish cities, Barcelona,Valencia and Vigo, for the period 1992–1994. Because the dependent variable was a count, a Poisson generalised linear model was first specified. Several modelling issues are worth mentioning. Firstly, because the relations between mortality and explanatory variables were nonlinear, cubic splines were used for covariate control, leading to a generalised additive model, GAM. Secondly, the effects of the predictors on the response were allowed to occur with some lag. Thirdly, the residual autocorrelation, because of imperfect control, was controlled for by means of an autoregressive Poisson GAM. Finally, the longitudinal design demanded the consideration of the existence of individual heterogeneity, requiring the consideration of mixed models. Main results—The estimates of the relative risks obtained from the individual analyses varied across cities, particularly those associated with sulphur dioxide. The highest relative risks corresponded to black smoke in Valencia. These estimates were higher than those obtained from the ecological-longitudinal analysis. Relative risks estimated from this latter analysis were practically identical across cities, 1.00638 (95% confidence intervals 1.0002, 1.0011) for a black smoke increase of 10 μg/m3 and 1.00415 (95% CI 1.0001, 1.0007) for a increase of 10 μg/m3 of sulphur dioxide. Because the statistical power is higher than in the individual analysis more interactions were statistically significant,especially those among air pollutants and meteorological variables. Conclusions—Air pollutant levels were related to mortality in the three cities of the study, Barcelona, Valencia and Vigo. These results were consistent with similar studies in other cities, with other multicentric studies and coherent with both, previous individual, for each city, and multicentric studies for all three cities

Measurement Quality in Indicators of Compositions: a Compositional Multitrait-Multimethod Approach

Compositional data, also called multiplicative ipsative data, are common in survey research instruments in areas such as time use, budget expenditure and social networks. Compositional data are usually expressed as proportions of a total, whose sum can only be 1. Owing to their constrained nature, statistical analysis in general, and estimation of measurement quality with a confirmatory factor analysis model for multitrait-multimethod (MTMM) designs in particular are challenging tasks. Compositional data are highly non-normal, as they range within the 0-1 interval. One component can only increase if some other(s) decrease, which results in spurious negative correlations among components which cannot be accounted for by the MTMM model parameters. In this article we show how researchers can use the correlated uniqueness model for MTMM designs in order to evaluate measurement quality of compositional indicators. We suggest using the additive log ratio transformation of the data, discuss several approaches to deal with zero components and explain how the interpretation of MTMM designs di ers from the application to standard unconstrained data. We show an illustration of the method on data of social network composition expressed in percentages of partner, family, friends and other members in which we conclude that the faceto-face collection mode is generally superior to the telephone mode, although primacy e ects are higher in the face-to-face mode. Compositions of strong ties (such as partner) are measured with higher quality than those of weaker ties (such as other network members)