Unbiased estimating equations from working correlation models for irregularly timed repeated measures

The method of generalized estimating equation-, (GEEs) has been criticized recently for a failure to protect against misspecification of working correlation models, which in some cases leads to loss of efficiency or infeasibility of solutions. However, the feasibility and efficiency of GEE methods can be enhanced considerably by using flexible families of working correlation models. We propose two ways of constructing unbiased estimating equations from general correlation models for irregularly timed repeated measures to supplement and enhance GEE. The supplementary estimating equations are obtained by differentiation of the Cholesky decomposition of the working correlation, or as score equations for decoupled Gaussian pseudolikelihood. The estimating equations are solved with computational effort equivalent to that required for a first-order GEE. Full details and analytic expressions are developed for a generalized Markovian model that was evaluated through simulation. Large-sample ".sandwich" standard errors for working correlation parameter estimates are derived and shown to have good performance. The proposed estimating functions are further illustrated in an analysis of repeated measures of pulmonary function in children.

Correlation models of diffuse solar-radiation applied to the city of São Paulo, Brazil

Measurements of global and diffuse solar-radiation, at the Earth's surface, carried out from May 1994 to June 1999 in São Paulo City, Brazil, were used to develop correlation models to estimate hourly, daily and monthly values of diffuse solar-radiation on horizontal surfaces. The polynomials derived by linear regression fitting were able to model satisfactorily the daily and monthly values of diffuse radiation. The comparison with models derived for other places demonstrates some differences related mainly to altitude effects. (C) 2002 Elsevier B.V. Ltd. All rights reserved.

Crude oil and agricultural futures: An analysis of correlation dynamics

Correlations between oil and agricultural commodities have varied over previous decades, impacted by renewable fuels policy and turbulent economic conditions. We estimate smooth transition conditional correlation models for 12 agricultural commodities and WTI crude oil. While a structural change in correlations occurred concurrently with the introduction of biofuel policy, oil and food price levels are also key influences. High correlation between biofuel feedstocks and oil is more likely to occur when food and oil price levels are high. Correlation with oil returns is strong for biofuel feedstocks, unlike with other agricultural futures, suggesting limited contagion from energy to food markets.

Dynamic conditional correlation in Latin-American asset markets

In this paper we reviewed the models of volatility for a group of five Latin American countries, mainly motivated by the recent periods of financial turbulence. Our results based on high frequency data suggest that Dynamic multivariate models are more powerful to study the volatilities of asset returns than Constant Conditional Correlation models. For the group of countries included, we identified that domestic volatilities of asset markets have been increasing; but the co-volatility of the region is still moderate.

In vitro-in vivo Pharmacokinetic correlation model for quality assurance of antiretroviral drugs

Introduction: The In vitro-in vivo pharmacokinetic correlation models (IVIVC) are a fundamental part of the drug discovery and development process. The ability to accurately predict the in vivo pharmacokinetic profile of a drug based on in vitro observations can have several applications during a successful development process. Objective: To develop a comprehensive model to predict the in vivo absorption of antiretroviral drugs based on permeability studies, in vitro and in vivo solubility and demonstrate its correlation with the pharmacokinetic profile in humans. Methods: Analytical tools to test the biopharmaceutical properties of stavudine, lamivudine y zidovudine were developed. The kinetics of dissolution, permeability in caco-2 cells and pharmacokinetics of absorption in rabbits and healthy volunteers were evaluated. Results: The cumulative areas under the curve (AUC) obtained in the permeability study with Caco-2 cells, the dissolution study and the pharmacokinetics in rabbits correlated with the cumulative AUC values in humans. These results demonstrated a direct relation between in vitro data and absorption, both in humans and in the in vivo model. Conclusions: The analytical methods and procedures applied to the development of an IVIVC model showed a strong correlation among themselves. These IVIVC models are proposed as alternative and cost/effective methods to evaluate the biopharmaceutical properties that determine the bioavailability of a drug and their application includes the development process, quality assurance, bioequivalence studies and pharmacosurveillance.

Efficient parameter estimation in longitudinal data analysis using a hybrid GEE method

The method of generalized estimating equations (GEEs) provides consistent estimates of the regression parameters in a marginal regression model for longitudinal data, even when the working correlation model is misspecified (Liang and Zeger, 1986). However, the efficiency of a GEE estimate can be seriously affected by the choice of the working correlation model. This study addresses this problem by proposing a hybrid method that combines multiple GEEs based on different working correlation models, using the empirical likelihood method (Qin and Lawless, 1994). Analyses show that this hybrid method is more efficient than a GEE using a misspecified working correlation model. Furthermore, if one of the working correlation structures correctly models the within-subject correlations, then this hybrid method provides the most efficient parameter estimates. In simulations, the hybrid method's finite-sample performance is superior to a GEE under any of the commonly used working correlation models and is almost fully efficient in all scenarios studied. The hybrid method is illustrated using data from a longitudinal study of the respiratory infection rates in 275 Indonesian children.

A modified pseudolikelihood approach for analysis of longitudinal data

We consider the analysis of longitudinal data when the covariance function is modeled by additional parameters to the mean parameters. In general, inconsistent estimators of the covariance (variance/correlation) parameters will be produced when the "working" correlation matrix is misspecified, which may result in great loss of efficiency of the mean parameter estimators (albeit the consistency is preserved). We consider using different "Working" correlation models for the variance and the mean parameters. In particular, we find that an independence working model should be used for estimating the variance parameters to ensure their consistency in case the correlation structure is misspecified. The designated "working" correlation matrices should be used for estimating the mean and the correlation parameters to attain high efficiency for estimating the mean parameters. Simulation studies indicate that the proposed algorithm performs very well. We also applied different estimation procedures to a data set from a clinical trial for illustration.

Stability of stochastic Leipholz column with stochastic loading

The Leipholz column which is having the Young modulus and mass per unit length as stochastic processes and also the distributed tangential follower load behaving stochastically is considered. The non self-adjoint differential equation and boundary conditions are considered to have random field coefficients. The standard perturbation method is employed. The non self-adjoint operators are used within the regularity domain. Full covariance structure of the free vibration eigenvalues and critical loads is derived in terms of second order properties of input random fields characterizing the system parameter fluctuations. The mean value of critical load is calculated using the averaged problem and the corresponding eigenvalue statistics are sought. Through the frequency equation a transformation is done to yield load parameter statistics. A numerical study incorporating commonly observed correlation models is reported which illustrates the full potentials of the derived expressions.

Electron impact excitation of xenon from the metastable state to the excited states

The electron impact excitation cross sections from the lowest metastable state 5p(5)6sJ = 2 to the six lowest excited states of the 5p(5)6p configuration of xenon are calculated systematically by using the fully relativistic distorted wave method. In order to discuss the effects of target state descriptions on the electron impact excitation cross sections, two correlation models are used to describe the target states based on the multiconfiguration Dirac-Fock (MCDF) method. It is found that the correlation effects play a very important role in low energy impact. For high energy impact, however, the cross sections are not sensitive to the description of the target states, but many more partial waves must be included.

Intrinsic measure of diversity gains in generalised distributed antenna systems with cooperative users

The diversity gains achievable in the generalised distributed antenna system with cooperative users (GDAS-CU) are considered. A GDAS-CU is comprised of M largely separated access points (APs) at one side of the link, and N geographically closed user terminals (UTs) at the other side. The UTs are collaborating together to enhance the system performance, where an idealised message sharing among the UTs is assumed. First, geometry-based network models are proposed to describe the topology of a GDAS-CU. The mean cross-correlation coefficients of signals received from non-collocated APs and UTs are calculated based on the network topology and the correlation models derived from the empirical data. The analysis is also extendable to more general scenarios where the APs are placed in a clustered form due to the constraints of street layout or building structure. Subsequently, a generalised signal attenuation model derived from several stochastic ray-tracing-based pathloss models is applied to describe the power-decaying pattern in urban built-up areas, where the GDAS-CU may be deployed. Armed with the cross-correlation and pathloss model preliminaries, an intrinsic measure of cooperative diversity obtainable from a GDAS-CU is then derived, which is the number of independent fading channels that can be averaged over to detect symbols. The proposed analytical framework would provide critical insight into the degree of possible performance improvement when combining multiple copies of the received signal in such systems.

Diffusion coefficients in dense and supercritical fluids

Os coeficientes de difusão (D 12) são propriedades fundamentais na investigação e na indústria, mas a falta de dados experimentais e a inexistência de equações que os estimem com precisão e confiança em fases comprimidas ou condensadas constituem limitações importantes. Os objetivos principais deste trabalho compreendem: i) a compilação de uma grande base de dados para valores de D 12 de sistemas gasosos, líquidos e supercríticos; ii) o desenvolvimento e validação de novos modelos de coeficientes de difusão a diluição infinita, aplicáveis em amplas gamas de temperatura e densidade, para sistemas contendo componentes muito distintos em termos de polaridade, tamanho e simetria; iii) a montagem e teste de uma instalação experimental para medir coeficientes de difusão em líquidos e fluidos supercríticos. Relativamente à modelação, uma nova expressão para coeficientes de difusão a diluição infinita de esferas rígidas foi desenvolvida e validada usando dados de dinâmica molecular (desvio relativo absoluto médio, AARD = 4.44%) Foram também estudados os coeficientes de difusão binários de sistemas reais. Para tal, foi compilada uma extensa base de dados de difusividades de sistemas reais em gases e solventes densos (622 sistemas binários num total de 9407 pontos experimentais e 358 moléculas) e a mesma foi usada na validação dos novos modelos desenvolvidos nesta tese. Um conjunto de novos modelos foi proposto para o cálculo de coeficientes de difusão a diluição infinita usando diferentes abordagens: i) dois modelos de base molecular com um parâmetro específico para cada sistema, aplicáveis em sistemas gasosos, líquidos e supercríticos, em que natureza do solvente se encontra limitada a apolar ou fracamente polar (AARDs globais na gama 4.26-4.40%); ii) dois modelos de base molecular biparamétricos, aplicáveis em todos os estados físicos, para qualquer tipo de soluto diluído em qualquer solvente (apolar, fracamente polar e polar). Ambos os modelos dão origem a erros globais entre 2.74% e 3.65%; iii) uma correlação com um parâmetro, específica para coeficientes de difusão em dióxido de carbono supercrítico (SC-CO2) e água líquida (AARD = 3.56%); iv) nove correlações empíricas e semi-empíricas que envolvem dois parâmetros, dependentes apenas da temperatura e/ou densidade do solvente e/ou viscosidade do solvente. Estes últimos modelos são muito simples e exibem excelentes resultados (AARDs entre 2.78% e 4.44%) em sistemas líquidos e supercríticos; e v) duas equações preditivas para difusividades de solutos em SC-CO2, em que os erros globais de ambas são inferiores a 6.80%. No global, deve realçar-se o facto de os novos modelos abrangerem a grande variedade de sistemas e moléculas geralmente encontrados. Os resultados obtidos são consistentemente melhores do que os obtidos com os modelos e abordagens encontrados na literatura. No caso das correlações com um ou dois parâmetros, mostrou-se que estes mesmos parâmetros podem ser ajustados usando um conjunto muito pequeno de dados, e posteriormente serem utilizados na previsão de valores de D 12 longe do conjunto original de pontos. Uma nova instalação experimental para medir coeficientes de difusão binários por técnicas cromatográficas foi montada e testada. O equipamento, o procedimento experimental e os cálculos analíticos necessários à obtenção dos valores de D 12 pelo método de abertura do pico cromatográfico, foram avaliados através da medição de difusividades de tolueno e acetona em SC-CO2. Seguidamente, foram medidos coeficientes de difusão de eucaliptol em SC-CO2 nas gamas de 202 – 252 bar e 313.15 – 333.15 K. Os resultados experimentais foram analisados através de correlações e modelos preditivos para D12.

Geographic Range Shifts under Climate Warming

Thesis (Ph.D.)--University of Washington, 2013

Stock return comovements and integration within the Latin American integrated market

Financial integration has been pursued aggressively across the globe in the last fifty years; however, there is no conclusive evidence on the diversification gains (or losses) of such efforts. These gains (or losses) are related to the degree of comovements and synchronization among increasingly integrated global markets. We quantify the degree of comovements within the integrated Latin American market (MILA). We use dynamic correlation models to quantify comovements across securities as well as a direct integration measure. Our results show an increase in comovements when we look at the country indexes, however, the increase in the trend of correlation is previous to the institutional efforts to establish an integrated market in the region. On the other hand, when we look at sector indexes and an integration measure, we find a decreased in comovements among a representative sample of securities form the integrated market.

Modeling hourly and daily fractions of UV, PAR and NIR to global solar radiation under various sky conditions at Botucatu, Brazil

In this analysis, using available hourly and daily radiometric data performed at Botucatu, Brazil, several empirical models relating ultraviolet (UV), photosynthetically active (PAR) and near infrared (NIR) solar global components with solar global radiation (G) are established. These models are developed and discussed through clearness index K(T) (ratio of the global-to-extraterrestrial solar radiation). Results obtained reveal that the proposed empirical models predict hourly and daily values accurately. Finally. the overall analysis carried Out demonstrates that the sky conditions are more important in developing correlation models between the UV component and the global solar radiation. The linear regression models derived to estimate PAR and NIR components may be obtained without sky condition considerations within a maximum variation of 8%. In the case of UV, not taking into consideration the sky condition may cause a discrepancy of up to 18% for hourly values and 15% for daily values. (C) 2008 Elsevier Ltd. All rights reserved.

The role of clouds in improving the regression model for hourly values of diffuse solar radiation

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)