Leverage analysis for linear mixed models

We consider a generalized leverage matrix useful for the identification of influential units and observations in linear mixed models and show how a decomposition of this matrix may be employed to identify high leverage points for both the marginal fitted values and the random effect component of the conditional fitted values. We illustrate the different uses of the two components of the decomposition with a simulated example as well as with a real data set.

On the skew-normal calibration model

In this article, we present the EM-algorithm for performing maximum likelihood estimation of an asymmetric linear calibration model with the assumption of skew-normally distributed error. A simulation study is conducted for evaluating the performance of the calibration estimator with interpolation and extrapolation situations. As one application in a real data set, we fitted the model studied in a dimensional measurement method used for calculating the testicular volume through a caliper and its calibration by using ultrasonography as the standard method. By applying this methodology, we do not need to transform the variables to have symmetrical errors. Another interesting aspect of the approach is that the developed transformation to make the information matrix nonsingular, when the skewness parameter is near zero, leaves the parameter of interest unchanged. Model fitting is implemented and the best choice between the usual calibration model and the model proposed in this article was evaluated by developing the Akaike information criterion, Schwarz`s Bayesian information criterion and Hannan-Quinn criterion.

A new class of survival regression models with heavy-tailed errors: robustness and diagnostics

Birnbaum-Saunders models have largely been applied in material fatigue studies and reliability analyses to relate the total time until failure with some type of cumulative damage. In many problems related to the medical field, such as chronic cardiac diseases and different types of cancer, a cumulative damage caused by several risk factors might cause some degradation that leads to a fatigue process. In these cases, BS models can be suitable for describing the propagation lifetime. However, since the cumulative damage is assumed to be normally distributed in the BS distribution, the parameter estimates from this model can be sensitive to outlying observations. In order to attenuate this influence, we present in this paper BS models, in which a Student-t distribution is assumed to explain the cumulative damage. In particular, we show that the maximum likelihood estimates of the Student-t log-BS models attribute smaller weights to outlying observations, which produce robust parameter estimates. Also, some inferential results are presented. In addition, based on local influence and deviance component and martingale-type residuals, a diagnostics analysis is derived. Finally, a motivating example from the medical field is analyzed using log-BS regression models. Since the parameter estimates appear to be very sensitive to outlying and influential observations, the Student-t log-BS regression model should attenuate such influences. The model checking methodologies developed in this paper are used to compare the fitted models.

Development of a sequential injection-square wave voltammetry method for determination of paraquat in water samples employing the hanging mercury drop electrode

This work describes the development and optimization of a sequential injection method to automate the determination of paraquat by square-wave voltammetry employing a hanging mercury drop electrode. Automation by sequential injection enhanced the sampling throughput, improving the sensitivity and precision of the measurements as a consequence of the highly reproducible and efficient conditions of mass transport of the analyte toward the electrode surface. For instance, 212 analyses can be made per hour if the sample/standard solution is prepared off-line and the sequential injection system is used just to inject the solution towards the flow cell. In-line sample conditioning reduces the sampling frequency to 44 h(-1). Experiments were performed in 0.10 M NaCl, which was the carrier solution, using a frequency of 200 Hz, a pulse height of 25 mV, a potential step of 2 mV, and a flow rate of 100 mu L s(-1). For a concentration range between 0.010 and 0.25 mg L(-1), the current (i(p), mu A) read at the potential corresponding to the peak maximum fitted the following linear equation with the paraquat concentration (mg L(-1)): ip = (-20.5 +/- 0.3) Cparaquat -(0.02 +/- 0.03). The limits of detection and quantification were 2.0 and 7.0 mu g L(-1), respectively. The accuracy of the method was evaluated by recovery studies using spiked water samples that were also analyzed by molecular absorption spectrophotometry after reduction of paraquat with sodium dithionite in an alkaline medium. No evidence of statistically significant differences between the two methods was observed at the 95% confidence level.

Development of a heavy metal sorption system through the P=S functionalization of coconut (Cocos nucifera) fibers

Lignocellulosic residues are interesting materials for the production of heavy metal adsorbents for aquatic systems. Whole fibers taken from coconut (Cocos nucifera) husks were functionalized with the thiophosphoryl (P=S) group by means of the direct reaction with CI(3)P=S, (CH(3)O)(2)CIP=S or (CH(3)CH(2)O)(2)CIP=S in order to obtain an adsorptive system for `soft` metal ions, particularly Cd(2+). These functionalized fibers (FFs) were characterized by means of elemental analysis, infrared spectroscopy, thermal analysis and acid-base titration. Adsorption isotherms for Cd(2+) fitted the Langmuir model, with binding capacities of 0.2-5 mmol g(-1) of FF at 25 degrees C. (C) 2009 Elsevier Ltd. All rights reserved.

Three-Dimensional Quantitative Structure-Activity Relationship Study of Antitumor 2-Formylpyridine Thiosemicarbazones Derivatives as Inhibitors of Ribonucleotide Reductase

In order to extend previous SAR and QSAR studies, 3D-QSAR analysis has been performed using CoMFA and CoMSIA approaches applied to a set of 39 alpha-(N)-heterocyclic carboxaldehydes thiosemicarbazones with their inhibitory activity values (IC(50)) evaluated against ribonucleotide reductase (RNR) of H.Ep.-2 cells (human epidermoid carcinoma), taken from selected literature. Both rigid and field alignment methods, taking the unsubstituted 2-formylpyridine thiosemicarbazone in its syn conformation as template, have been used to generate multiple predictive CoMFA and CoMSIA models derived from training sets and validated with the corresponding test sets. Acceptable predictive correlation coefficients (Q(cv)(2) from 0.360 to 0.609 for CoMFA and Q(cv)(2) from 0.394 to 0.580 for CoMSIA models) with high fitted correlation coefficients (r` from 0.881 to 0.981 for CoMFA and r(2) from 0.938 to 0.993 for CoMSIA models) and low standard errors (s from 0.135 to 0.383 for CoMFA and s from 0.098 to 0.240 for CoMSIA models) were obtained. More precise CoMFA and CoMSIA models have been derived considering the subset of thiosemicarbazones (TSC) substituted only at 5-position of the pyridine ring (n=22). Reasonable predictive correlation coefficients (Q(cv)(2) from 0.486 to 0.683 for CoMFA and Q(cv)(2) from 0.565 to 0.791 for CoMSIA models) with high fitted correlation coefficients (r(2) from 0.896 to 0.997 for CoMFA and r(2) from 0.991 to 0.998 for CoMSIA models) and very low standard errors (s from 0.040 to 0.179 for CoMFA and s from 0.029 to 0.068 for CoMSIA models) were obtained. The stability of each CoMFA and CoMSIA models was further assessed by performing bootstrapping analysis. For the two sets the generated CoMSIA models showed, in general, better statistics than the corresponding CoMFA models. The analysis of CoMFA and CoMSIA contour maps suggest that a hydrogen bond acceptor near the nitrogen of the pyridine ring can enhance inhibitory activity values. This observation agrees with literature data, which suggests that the nitrogen pyridine lone pairs can complex with the iron ion leading to species that inhibits RNR. The derived CoMFA and CoMSIA models contribute to understand the structural features of this class of TSC as antitumor agents in terms of steric, electrostatic, hydrophobic and hydrogen bond donor and hydrogen bond acceptor fields as well as to the rational design of this key enzyme inhibitors.

Developing a fluorimetric sequential injection methodology to study adsorption/desorption of glyphosate on soil and sediment samples

This paper describes the development of a sequential injection method to automate the fluorimetric determination of glyphosate based on a first step of oxidation to glycine by hypochlorite at 48 degrees C, followed by reaction with the fluorogenic reagent o-phthaldialdehyde in presence of 2-mercaptoethanol in borate buffer (pH > 9) to produce a fluorescent 1-(2`-hydroxyethylthio)-2-N-alkylisoindole. The proposed method has a linear response for glyphosate concentrations between 0.25 and 25.0 mu mol L(-1), with limits of detection and quantification of 0.08 and 0.25 mu mol L(-1), respectively. The sampling rate of the method is 18 samples per hour, consuming only a fraction of reagents consumed by the chromatographic method based on the same chemistry. The method was applied to study adsorption/desorption properties in a soil and in a sediment sample. Adsorption and desorption isotherms were properly fitted by Freundlich and Langmuir equations, leading to adsorption capacities of 1384 +/- 26 and 295 +/- 30 mg kg(-1) for the soil and sediment samples, respectively. These values are consistent with the literature, with the larger adsorption capacity of the soil being explained by its larger content of clay minerals, while the sediment was predominantly sandy. (C) 2011 Elsevier B.V. All rights reserved.

Inactivation kinetics of polyphenol oxidase and peroxidase in green coconut water by microwave processing

The inactivation kinetics of enzymes polyphenol oxidase (PPO) and peroxidase (POD) was studied for the batch (discontinuous) microwave treatment of green coconut water. Inactivation of commercial PPO and POD added to sterile coconut water was also investigated. The complete time-temperature profiles of the experimental runs were used for determination of the kinetic parameters D-value and z-value: PPO (D(92.20 degrees C) = 52 s and z = 17.6 degrees C); POD (D(92.92 degrees C) = 16 s and z = 11.5 degrees C); PPO/sterile coconut water: (D(84.45 degrees C) = 43 s and z = 39.5 degrees C) and POD/sterile coconut water: (D(86.54 degrees C) = 20 s and z = 19.3 degrees C). All data were well fitted by a first order kinetic model. The enzymes naturally present in coconut water showed a higher resistance when compared to those added to the sterilized medium or other simulated solutions reported in the literature. The thermal inactivation of PPO and POD during microwave processing of green coconut water was significantly faster in comparison with conventional processes reported in the literature. (C) 2008 Elsevier Ltd. All rights reserved.

Adsorption of di-2-pyridyl ketone salicyloylhydrazone on Amberlite XAD-2 and XAD-7 resins: Characteristics and isotherms

The adsorption of DPKSH onto Amberlite XAD-2 (styrene resin) and XAD-7 (acrylic ester resin) has been investigated, at (25 +/- 1)degrees C and pH 4.7. The experimental equilibrium data were fitted to the Langmuir, Freundlich, and Dubinin-Radushkevich (D-R) models. These three models provide a very good fit for both resins and the respective constants K(L), K(F), and K(DR) were calculated. For the same DPKSH concentration interval, the minimum time of contact for adsorption maximum at XAD-7 was smaller than at XAD-2 and the maximum amount of DPKSH adsorbed per gram of XAD-2 is smaller than at XAD-7. The investigation indicates that the mean sorption energy (E) characterizes a physical adsorption and the surfaces of both resins are energetically heterogeneous. The constants obtained in these studied systems were correlated and compared with those obtained for the silica gel/DPKSH system. (C) 2008 Published by Elsevier Inc.

Hglm: A package for fitting hierarchical generalized linear models

We present the hglm package for fitting hierarchical generalized linear models. It can be used for linear mixed models and generalized linear mixed models with random effects for a variety of links and a variety of distributions for both the outcomes and the random effects. Fixed effects can also be fitted in the dispersion part of the model.

Genetic heterogeneity of residual variance : estimation of variance components using double hierarchical generalized linear models

Background: The sensitivity to microenvironmental changes varies among animals and may be under genetic control. It is essential to take this element into account when aiming at breeding robust farm animals. Here, linear mixed models with genetic effects in the residual variance part of the model can be used. Such models have previously been fitted using EM and MCMC algorithms. Results: We propose the use of double hierarchical generalized linear models (DHGLM), where the squared residuals are assumed to be gamma distributed and the residual variance is fitted using a generalized linear model. The algorithm iterates between two sets of mixed model equations, one on the level of observations and one on the level of variances. The method was validated using simulations and also by re-analyzing a data set on pig litter size that was previously analyzed using a Bayesian approach. The pig litter size data contained 10,060 records from 4,149 sows. The DHGLM was implemented using the ASReml software and the algorithm converged within three minutes on a Linux server. The estimates were similar to those previously obtained using Bayesian methodology, especially the variance components in the residual variance part of the model. Conclusions: We have shown that variance components in the residual variance part of a linear mixed model can be estimated using a DHGLM approach. The method enables analyses of animal models with large numbers of observations. An important future development of the DHGLM methodology is to include the genetic correlation between the random effects in the mean and residual variance parts of the model as a parameter of the DHGLM.

Fitting spatial models in the R package: hglm

We present a new version of the hglm package for fittinghierarchical generalized linear models (HGLM) with spatially correlated random effects. A CAR family for conditional autoregressive random effects was implemented. Eigen decomposition of the matrix describing the spatial structure (e.g. the neighborhood matrix) was used to transform the CAR random effectsinto an independent, but heteroscedastic, gaussian random effect. A linear predictor is fitted for the random effect variance to estimate the parameters in the CAR model.This gives a computationally efficient algorithm for moderately sized problems (e.g. n<5000).

Fitting conditional and simultaneous autoregressive spatial models in hglm

We present a new version (> 2.0) of the hglm package for fitting hierarchical generalized linear models (HGLMs) with spatially correlated random effects. CAR() and SAR() families for conditional and simultaneous autoregressive random effects were implemented. Eigen decomposition of the matrix describing the spatial structure (e.g., the neighborhood matrix) was used to transform the CAR/SAR random effects into an independent, but eteroscedastic, Gaussian random effect. A linear predictor is fitted for the random effect variance to estimate the parameters in the CAR and SAR models. This gives a computationally efficient algorithm for moderately sized problems.

An Empirical Study on Teachers’ Choice of Extensive Literature in the Swedish Upper Secondary EFL Classroom

The importance of extensive literature reading in the English as a Foreign Language (EFL) context has been given increasing attention in recent research. Literature reading is also a required part of the national syllabi of the (EFL) courses offered to both adolescents and adults at Upper Secondary level in Sweden. This thesis aims to investigate the teachers’ process of making literature choices for extensive reading in upper secondary EFL courses in Sweden. Eight teachers of three different student groups took part in the study, representing adolescent university preparatory programs and vocational programs, as well as programs for adult students. Questionnaires were used and the data was analyzed for patterns revealing three main factors affecting teachers’ literature choice: language proficiency, reading experience and contextual factors. These three factors were fitted into the theoretical framework of psycholinguistic and sociolinguistic reading models, with the addition of a perspective of motivational research. The results of this survey underline the importance of extensive reading, according to teachers, and that motivation for literature choice can be primarily related to factors associated with psycholinguistic reading models. The survey also points to the need for further investigating of teachers’ own experiences of literature reading, searching for deeper motivational factors which influence teaching choices. Another future field of research is the choice of reading activities assigned together with the chosen literature, which probably also influence teachers’ choices in the Swedish EFL classroom.

A metodologia de análise de dados espaciais aplicada a plantas forrageiras

Dois experimentos e um levantamento por amostragem foram analisados no contexto de dados espaciais. Os experimentos foram delineados em blocos completos casualizados sendo que no experimento um (EXP 1) foram avaliados oito cultivares de trevo branco, sendo estudadas as variáveis Matéria Seca Total (MST) e Matéria Seca de Gramíneas (MSGRAM) e no experimento dois (EXP 2) 20 cultivares de espécies forrageiras, onde foi estudada a variável Percentagem de Implantação (%IMPL). As variáveis foram analisadas no contexto de modelos mistos, sendo modelada a variabilidade espacial através de semivariogramas exponencias, esféricos e gaussianos. Verificou-se uma diminuição em média de 19% e 14% do Coeficiente de Variação (CV) das medias dos cultivares, e uma diminuição em média de 24,6% e 33,3% nos erros padrões dos contrastes ortogonais propostos em MST e MSGRAM. No levantamento por amostragem, estudou-se a associação espacial em Aristida laevis (Nees) Kunth , Paspalum notatum Fl e Demodium incanum DC, amostrados em uma transecção fixa de quadros contiguos, a quatro tamanhos de unidades amostrais (0,1x0,1m; 0,1x0,3m; 0,1x0,5m; e 0,1x1,0m). Nas espécies Aristida laevis (Nees) Kunth e Paspalum notatum Fl, existiu um bom ajuste dos semivariogramas a tamanhos menores das unidades amostrais, diminuíndo quando a unidade amostral foi maior. Desmodium incanum DC apresentou comportamento contrario, ajustando melhor os semivariogramas a tamanhos maiores das unidades amostrais.