Multiple imputation for missing continuous and dichotomous data: The effects of patterns of missingness and variable correlations on type I error with small samples

The purpose of this study is to investigate the effects of predictor variable correlations and patterns of missingness with dichotomous and/or continuous data in small samples when missing data is multiply imputed. Missing data of predictor variables is multiply imputed under three different multivariate models: the multivariate normal model for continuous data, the multinomial model for dichotomous data and the general location model for mixed dichotomous and continuous data. Subsequent to the multiple imputation process, Type I error rates of the regression coefficients obtained with logistic regression analysis are estimated under various conditions of correlation structure, sample size, type of data and patterns of missing data. The distributional properties of average mean, variance and correlations among the predictor variables are assessed after the multiple imputation process. ^ For continuous predictor data under the multivariate normal model, Type I error rates are generally within the nominal values with samples of size n = 100. Smaller samples of size n = 50 resulted in more conservative estimates (i.e., lower than the nominal value). Correlation and variance estimates of the original data are retained after multiple imputation with less than 50% missing continuous predictor data. For dichotomous predictor data under the multinomial model, Type I error rates are generally conservative, which in part is due to the sparseness of the data. The correlation structure for the predictor variables is not well retained on multiply-imputed data from small samples with more than 50% missing data with this model. For mixed continuous and dichotomous predictor data, the results are similar to those found under the multivariate normal model for continuous data and under the multinomial model for dichotomous data. With all data types, a fully-observed variable included with variables subject to missingness in the multiple imputation process and subsequent statistical analysis provided liberal (larger than nominal values) Type I error rates under a specific pattern of missing data. It is suggested that future studies focus on the effects of multiple imputation in multivariate settings with more realistic data characteristics and a variety of multivariate analyses, assessing both Type I error and power. ^

EFFECTS OF TETRAHYDROCANNABINOL ON SEXUAL DIMORPHISM OF RAT LIVER MIXED FUNCTION OXIDASE

Pregnant Sprague-Dawley rats were gavaged with vehicle (olive oil) or 37.5, 75, 150 or 300 mg/kg of (DELTA)('9)-Tetrahydrocannabinol (THC) on days 18 or 19 of gestation. Male offspring as well as a group of hypophysectomized rats (positive control) were sacrificed at 35 days of age, while females and hypophysectomized control were sacrificed at 36 days of age. The sex-differences in ethylmorphine-N-demethylase and aniline hydroxylase liver activities were evaluated.^ Ethylmorphine-N-demethylase activity showed a significant difference between males and females from control and 37.5, 75 and 150 mg/kg THC dosed groups. Female offspring exposed prenatally to 300 mg/kg THC had a significant increase (p < .01) in N-demethylation activity, while their male counterparts had similar enzyme activity to those found in the male groups from control and 37.5 to 150 mg/kg THC dosed. Moreover, the percent increase in the 300 mg/kg THC dosed females was similar to that detected in the hypophysectomized female rats (positive control). As expected no sex difference in aniline hydroxylase activity was detected in control as well as exposed groups, including the 300 mg/kg THC dosed group.^ It is concluded that (DELTA)('9)-Tetrahydrocannabinol administered once by gavage in days 18 or 19 of gestation alters the liver Mixed Function Oxidase (MFO) sexual dimorphism imprinting process of the rat. ^

Evaluation of the Hosmer -Lemeshow global goodness -of-fit statistic for mixed variable logistic regression models

The performance of the Hosmer-Lemeshow global goodness-of-fit statistic for logistic regression models was explored in a wide variety of conditions not previously fully investigated. Computer simulations, each consisting of 500 regression models, were run to assess the statistic in 23 different situations. The items which varied among the situations included the number of observations used in each regression, the number of covariates, the degree of dependence among the covariates, the combinations of continuous and discrete variables, and the generation of the values of the dependent variable for model fit or lack of fit.^ The study found that the $\rm\ C$g* statistic was adequate in tests of significance for most situations. However, when testing data which deviate from a logistic model, the statistic has low power to detect such deviation. Although grouping of the estimated probabilities into quantiles from 8 to 30 was studied, the deciles of risk approach was generally sufficient. Subdividing the estimated probabilities into more than 10 quantiles when there are many covariates in the model is not necessary, despite theoretical reasons which suggest otherwise. Because it does not follow a X$\sp2$ distribution, the statistic is not recommended for use in models containing only categorical variables with a limited number of covariate patterns.^ The statistic performed adequately when there were at least 10 observations per quantile. Large numbers of observations per quantile did not lead to incorrect conclusions that the model did not fit the data when it actually did. However, the statistic failed to detect lack of fit when it existed and should be supplemented with further tests for the influence of individual observations. Careful examination of the parameter estimates is also essential since the statistic did not perform as desired when there was moderate to severe collinearity among covariates.^ Two methods studied for handling tied values of the estimated probabilities made only a slight difference in conclusions about model fit. Neither method split observations with identical probabilities into different quantiles. Approaches which create equal size groups by separating ties should be avoided. ^

Analysis of Chromatic Aberration Effects in Triple-Junction Solar Cells Using Advanced Distributed Models

The consideration of real operating conditions for the design and optimization of a multijunction solar cell receiver-concentrator assembly is indispensable. Such a requirement involves the need for suitable modeling and simulation tools in order to complement the experimental work and circumvent its well-known burdens and restrictions. Three-dimensional distributed models have been demonstrated in the past to be a powerful choice for the analysis of distributed phenomena in single- and dual-junction solar cells, as well as for the design of strategies to minimize the solar cell losses when operating under high concentrations. In this paper, we present the application of these models for the analysis of triple-junction solar cells under real operating conditions. The impact of different chromatic aberration profiles on the short-circuit current of triple-junction solar cells is analyzed in detail using the developed distributed model. Current spreading conditions the impact of a given chromatic aberration profile on the solar cell I-V curve. The focus is put on determining the role of current spreading in the connection between photocurrent profile, subcell voltage and current, and semiconductor layers sheet resistance.

Some past decision theory models for euro construction model codes and for road drainage in Spain, and modest hints with multi-criteria methods for agro and environmental assurance

The authors are from UPM and are relatively grouped, and all have intervened in different academic or real cases on the subject, at different times as being of different age. With precedent from E. Torroja and A. Páez in Madrid Spain Safety Probabilistic models for concrete about 1957, now in ICOSSAR conferences, author J.M. Antón involved since autumn 1967 for euro-steel construction in CECM produced a math model for independent load superposition reductions, and using it a load coefficient pattern for codes in Rome Feb. 1969, practically adopted for European constructions, giving in JCSS Lisbon Feb. 1974 suggestion of union for concrete-steel-al.. That model uses model for loads like Gumbel type I, for 50 years for one type of load, reduced to 1 year to be added to other independent loads, the sum set in Gumbel theories to 50 years return period, there are parallel models. A complete reliability system was produced, including non linear effects as from buckling, phenomena considered somehow in actual Construction Eurocodes produced from Model Codes. The system was considered by author in CEB in presence of Hydraulic effects from rivers, floods, sea, in reference with actual practice. When redacting a Road Drainage Norm in MOPU Spain an optimization model was realized by authors giving a way to determine the figure of Return Period, 10 to 50 years, for the cases of hydraulic flows to be considered in road drainage. Satisfactory examples were a stream in SE of Spain with Gumbel Type I model and a paper of Ven Te Chow with Mississippi in Keokuk using Gumbel type II, and the model can be modernized with more varied extreme laws. In fact in the MOPU drainage norm the redacting commission acted also as expert to set a table of return periods for elements of road drainage, in fact as a multi-criteria complex decision system. These precedent ideas were used e.g. in wide Codes, indicated in symposia or meetings, but not published in journals in English, and a condensate of contributions of authors is presented. The authors are somehow involved in optimization for hydraulic and agro planning, and give modest hints of intended applications in presence of agro and environment planning as a selection of the criteria and utility functions involved in bayesian, multi-criteria or mixed decision systems. Modest consideration is made of changing in climate, and on the production and commercial systems, and on others as social and financial.

Impact attribution models to evaluate drought effects: economic impacts, risk analyses and management strategies in Spain and Chile

La sequía es un fenómeno natural que se origina por el descenso de las precipitaciones con respecto a una media, y que resulta en la disponibilidad insuficiente de agua para alguna actividad. La creciente presión que se ha venido ejerciendo sobre los recursos hídricos ha hecho que los impactos de la sequía se hayan visto agravados a la vez que ha desencadenado situaciones de escasez de agua en muchas partes del planeta. Los países con clima mediterráneo son especialmente vulnerables a las sequías, y, su crecimiento económico dependiente del agua da lugar a impactos importantes. Para reducir los impactos de la sequía es necesaria una reducción de la vulnerabilidad a las sequías que viene dada por una gestión más eficiente y por una mejor preparación. Para ello es muy importante disponer de información acerca de los impactos y el alcance de este fenómeno natural. Esta investigación trata de abarcar el tema de los impactos de las sequías, de manera que plantea todos los tipos de impactos que pueden darse y además compara sus efectos en dos países (España y Chile). Para ello se proponen modelos de atribución de impactos que sean capaces de medir las pérdidas económicas causadas por la falta de agua. Los modelos propuestos tienen una base econométrica en la que se incluyen variables clave a la hora de evaluar los impactos como es una variable relacionada con la disponibilidad de agua, y otras de otra naturaleza para distinguir los efectos causados por otras fuentes de variación. Estos modelos se adaptan según la fase del estudio en la que nos encontremos. En primer lugar se miden los impactos directos sobre el regadío y se introduce en el modelo un factor de aleatoriedad para evaluar el riesgo económico de sequía. Esto se hace a dos niveles geográficos (provincial y de Unidad de Demanda Agraria) y además en el último se introduce no solo el riesgo de oferta sino también el riesgo de demanda de agua. La introducción de la perspectiva de riesgo en el modelo da lugar a una herramienta de gestión del riesgo económico que puede ser utilizada para estrategias de planificación. Más adelante una extensión del modelo econométrico se desarrolla para medir los impactos en el sector agrario (impactos directos sobre el regadío y el secano e impactos indirectos sobre la Agro Industria) para ello se adapta el modelo y se calculan elasticidades concatenadas entre la falta de agua y los impactos secundarios. Por último se plantea un modelo econométrico para el caso de estudio en Chile y se evalúa el impacto de las sequías debidas al fenómeno de La Niña. iv Los resultados en general muestran el valor que brinda el conocimiento más preciso acerca de los impactos, ya que en muchas ocasiones se tiende a sobreestimar los daños realmente producidos por la falta de agua. Los impactos indirectos de la sequía confirman su alcance a la vez que son amortiguados a medida que nos acercamos al ámbito macroeconómico. En el caso de Chile, su diferente gestión muestra el papel que juegan el fenómeno de El Niño y La Niña sobre los precios de los principales cultivos del país y sobre el crecimiento del sector. Para reducir las pérdidas y su alcance se deben plantear más medidas de mitigación que centren su esfuerzo en una gestión eficiente del recurso. Además la prevención debe jugar un papel muy importante para reducir los riesgos que pueden sufrirse ante situaciones de escasez. ABSTRACT Drought is a natural phenomenon that originates by the decrease in rainfall in comparison to the average, and that results in water shortages for some activities. The increasing pressure on water resources has augmented the impact of droughts just as water scarcity has become an additional problem in many parts of the planet. Countries with Mediterranean climate are especially vulnerable to drought, and its waterdependent economic growth leads to significant impacts. To reduce the negative impacts it is necessary to deal with drought vulnerability, and to achieve this objective a more efficient management is needed. The availability of information about the impacts and the scope of droughts become highly important. This research attempts to encompass the issue of drought impacts, and therefore it characterizes all impact types that may occur and also compares its effects in two different countries (Spain and Chile). Impact attribution models are proposed in order to measure the economic losses caused by the lack of water. The proposed models are based on econometric approaches and they include key variables for measuring the impacts. Variables related to water availability, crop prices or time trends are included to be able to distinguish the effects caused by any of the possible sources. These models are adapted for each of the parts of the study. First, the direct impacts on irrigation are measured and a source of variability is introduced into the model to assess the economic risk of drought. This is performed at two geographic levels provincial and Agricultural Demand Unit. In the latter, not only the supply risk is considered but also the water demand risk side. The introduction of the risk perspective into the model results in a risk management tool that can be used for planning strategies. Then an extension of the econometric model is developed to measure the impacts on the agricultural sector (direct impacts on irrigated and rainfed productions and indirect impacts on the Agri-food Industry). For this aim the model is adapted and concatenated elasticities between the lack of water and the impacts are estimated. Finally an econometric model is proposed for the Chilean case study to evaluate the impact of droughts, especially caused by El Niño Southern Oscillation. The overall results show the value of knowing better about the precise impacts that often tend to be overestimated. The models allow for measuring accurate impacts due to the lack of water. Indirect impacts of drought confirm their scope while they confirm also its dilution as we approach the macroeconomic variables. In the case of Chile, different management strategies of the country show the role of ENSO phenomena on main crop prices and on economic trends. More mitigation measures focused on efficient resource management are necessary to reduce drought losses. Besides prevention must play an important role to reduce the risks that may be suffered due to shortages.

An empirical mixed model to quantify climate influence on the growth of Pinus halepensis Mill. stands in South-Eastern Spain

The influence of climate on forest stand composition, development and growth is undeniable. Many studies have tried to quantify the effect of climatic variables on forest growth and yield. These works become especially important because there is a need to predict the effects of climate change on the development of forest ecosystems. One of the ways of facing this problem is the inclusion of climatic variables into the classic empirical growth models. The work has a double objective: (i) to identify the indicators which best describe the effect of climate on Pinus halepensis growth and (ii) to quantify such effect in several scenarios of rainfall decrease which are likely to occur in the Mediterranean area. A growth mixed model for P. halepensis including climatic variables is presented in this work. Growth estimates are based on data from the Spanish National Forest Inventory (SNFI). The best results are obtained for the indices including rainfall, or rainfall and temperature together, with annual precipitation, precipitation effectiveness, Emberger?s index or free bioclimatic intensity standing out among them. The final model includes Emberger?s index, free bioclimatic intensity and interactions between competition and climate indices. The results obtained show that a rainfall decrease about 5% leads to a decrease in volume growth of 5.5?7.5% depending on site quality.

Asymptotic Description of Flutter Amplitude Saturation by Nonlinear Friction Forces

The computation of the non-linear vibration dynamics of an aerodynamically unstable bladed-disk is a formidable numerical task, even for the simplified case of aerodynamic forces assumed to be linear. The nonlinear friction forces effectively couple dif- ferent travelling waves modes and, in order to properly elucidate the dynamics of the system, large time simulations are typically required to reach a final, saturated state. Despite of all the above complications, the output of the system (in the friction microslip regime) is basically a superposition of the linear aeroelastic un- stable travelling waves, which exhibit a slow time modulation that is much longer than the elastic oscillation period. This slow time modulation is due to both, the small aerodynamic effects and the small nonlinear friction forces, and it is crucial to deter- mine the final amplitude of the flutter vibration. In this presenta- tion we apply asymptotic techniques to obtain a new simplified model that captures the slow time dynamics of the amplitudes of the travelling waves. The resulting asymptotic model is very re- duced and extremely cheap to simulate, and it has the advantage that it gives precise information about the characteristics of the nonlinear friction models that actually play a role in the satura- tion of the vibration amplitude.

Improving automatic detection of obstructive sleep apnea through nonlinear analysis of sustained speech

We present a novel approach for the detection of severe obstructive sleep apnea (OSA) based on patients' voices introducing nonlinear measures to describe sustained speech dynamics. Nonlinear features were combined with state-of-the-art speech recognition systems using statistical modeling techniques (Gaussian mixture models, GMMs) over cepstral parameterization (MFCC) for both continuous and sustained speech. Tests were performed on a database including speech records from both severe OSA and control speakers. A 10 % relative reduction in classification error was obtained for sustained speech when combining MFCC-GMM and nonlinear features, and 33 % when fusing nonlinear features with both sustained and continuous MFCC-GMM. Accuracy reached 88.5 % allowing the system to be used in OSA early detection. Tests showed that nonlinear features and MFCCs are lightly correlated on sustained speech, but uncorrelated on continuous speech. Results also suggest the existence of nonlinear effects in OSA patients' voices, which should be found in continuous speech.

Coupled models for the dynamics of bridges under high-speed rail traffic

The dynamic effects of high-speed trains on viaducts are important issues for the design of the structures, as well as for determining safe running conditions of trains. In this work we start by reviewing the relevance of some basic moving load models for the dynamic action of vertical traffic loads. The study of lateral dynamics of running trains on bridges is of importance mainly for the safety of the traffic, and may be relevant for laterally compliant bridges. These studies require 3D coupled vehicle-bridge models and consideration of wheel to rail contact. We describe here a fully nonlinear coupled model, formulated in absolute coordinates and incorporated into a commercial finite element framework. An application example is presented for a vehicle subject to a strong wind gust traversing a bridge, showing the relevance of the nonlinear wheel-rail contact model as well as the interaction between bridge and vehicle.

Asymptotic Description of Flutter Amplitude Saturation by Nonlinear Friction Forces

The computation of the non-linear vibration dynamics of an aerodynamically unstable bladed-disk is a formidable numerical task, even for the simplified case of aerodynamic forces assumed to be linear. The nonlinear friction forces effectively couple dif- ferent travelling waves modes and, in order to properly elucidate the dynamics of the system, large time simulations are typically required to reach a final, saturated state. Despite of all the above complications, the output of the system (in the friction microslip regime) is basically a superposition of the linear aeroelastic un- stable travelling waves, which exhibit a slow time modulation that is much longer than the elastic oscillation period. This slow time modulation is due to both, the small aerodynamic effects and the small nonlinear friction forces, and it is crucial to deter- mine the final amplitude of the flutter vibration. In this presenta- tion we apply asymptotic techniques to obtain a new simplified model that captures the slow time dynamics of the amplitudes of the travelling waves. The resulting asymptotic model is very re- duced and extremely cheap to simulate, and it has the advantage that it gives precise information about the characteristics of the nonlinear friction models that actually play a role in the satura- tion of the vibration amplitude.

Analysis and validation of CFD wind farm models in complex terrain. Effects induced by topography and wind turbines

Wind farms have been extensively simulated through engineering models for the estimation of wind speed and power deficits inside wind farms. These models were designed initially for a few wind turbines located in flat terrain. Other models based on the parabolic approximation of Navier Stokes equations were developed, making more realistic and feasible the operational resolution of big wind farms in flat terrain and offshore sites. These models have demonstrated to be accurate enough when solving wake effects for this type of environments. Nevertheless, few analyses exist on how complex terrain can affect the behaviour of wind farm wake flow. Recent numerical studies have demonstrated that topographical wakes induce a significant effect on wind turbines wakes, compared to that on flat terrain. This circumstance has recommended the development of elliptic CFD models which allow global simulation of wind turbine wakes in complex terrain. An accurate simplification for the analysis of wind turbine wakes is the actuator disk technique. Coupling this technique with CFD wind models enables the estimation of wind farm wakes preserving the extraction of axial momentum present inside wind farms. This paper describes the analysis and validation of the elliptical wake model CFDWake 1.0 against experimental data from an operating wind farm located in complex terrain. The analysis also reports whether it is possible or not to superimpose linearly the effect of terrain and wind turbine wakes. It also represents one of the first attempts to observe the performance of engineering models compares in large complex terrain wind farms.

Damping models in the truncated derivative nonlinear Schrödinger equation

Four-dimensional flow in the phase space of three amplitudes of circularly polarized Alfven waves and one relative phase, resulting from a resonant three-wave truncation of the derivative nonlinear Schrödinger equation, has been analyzed; wave 1 is linearly unstable with growth rate , and waves 2 and 3 are stable with damping 2 and 3, respectively. The dependence of gross dynamical features on the damping model as characterized by the relation between damping and wave-vector ratios, 2 /3, k2 /k3, and the polarization of the waves, is discussed; two damping models, Landau k and resistive k2, are studied in depth. Very complex dynamics, such as multiple blue sky catastrophes and chaotic attractors arising from Feigenbaum sequences, and explosive bifurcations involving Intermittency-I chaos, are shown to be associated with the existence and loss of stability of certain fixed point P of the flow. Independently of the damping model, P may only exist as against flow contraction just requiring.In the case of right-hand RH polarization, point P may exist for all models other than Landau damping; for the resistive model, P may exist for RH polarization only if 2+3/2.

First order mem-circuits: modeling, nonlinear oscillations and bifurcations

This paper presents a theoretical framework intended to accommodate circuit devices described by characteristics involving more than two fundamental variables. This framework is motivated by the recent appearance of a variety of so-called mem-devices in circuit theory, and makes it possible to model the coexistence of memory effects of different nature in a single device. With a compact formalism, this setting accounts for classical devices and also for circuit elements which do not admit a two-variable description. Fully nonlinear characteristics are allowed for all devices, driving the analysis beyond the framework of Chua and Di Ventra We classify these fully nonlinear circuit elements in terms of the variables involved in their constitutive relations and the notions of the differential- and the state-order of a device. We extend the notion of a topologically degenerate configuration to this broader context, and characterize the differential-algebraic index of nodal models of such circuits. Additionally, we explore certain dynamical features of mem-circuits involving manifolds of non-isolated equilibria. Related bifurcation phenomena are explored for a family of nonlinear oscillators based on mem-devices.