Bayesian Estimation of the Logistic Positive Exponent IRT Model

A Bayesian inference approach using Markov Chain Monte Carlo (MCMC) is developed for the logistic positive exponent (LPE) model proposed by Samejima and for a new skewed Logistic Item Response Theory (IRT) model, named Reflection LPE model. Both models lead to asymmetric item characteristic curves (ICC) and can be appropriate because a symmetric ICC treats both correct and incorrect answers symmetrically, which results in a logical contradiction in ordering examinees on the ability scale. A data set corresponding to a mathematical test applied in Peruvian public schools is analyzed, where comparisons with other parametric IRT models also are conducted. Several model comparison criteria are discussed and implemented. The main conclusion is that the LPE and RLPE IRT models are easy to implement and seem to provide the best fit to the data set considered.

Bayesian estimation of regression parameters in elliptical measurement error models

The main object of this paper is to discuss the Bayes estimation of the regression coefficients in the elliptically distributed simple regression model with measurement errors. The posterior distribution for the line parameters is obtained in a closed form, considering the following: the ratio of the error variances is known, informative prior distribution for the error variance, and non-informative prior distributions for the regression coefficients and for the incidental parameters. We proved that the posterior distribution of the regression coefficients has at most two real modes. Situations with a single mode are more likely than those with two modes, especially in large samples. The precision of the modal estimators is studied by deriving the Hessian matrix, which although complicated can be computed numerically. The posterior mean is estimated by using the Gibbs sampling algorithm and approximations by normal distributions. The results are applied to a real data set and connections with results in the literature are reported. (C) 2011 Elsevier B.V. All rights reserved.

Reliability Nonparametric Bayesian Estimation in Parallel Systems

Relevant results for (sub-)distribution functions related to parallel systems are discussed. The reverse hazard rate is defined using the product integral. Consequently, the restriction of absolute continuity for the involved distributions can be relaxed. The only restriction is that the sets of discontinuity points of the parallel distributions have to be disjointed. Nonparametric Bayesian estimators of all survival (sub-)distribution functions are derived. Dual to the series systems that use minimum life times as observations, the parallel systems record the maximum life times. Dirichlet multivariate processes forming a class of prior distributions are considered for the nonparametric Bayesian estimation of the component distribution functions, and the system reliability. For illustration, two striking numerical examples are presented.

A semi-Markov multistate model for estimation of the mean quality-adjusted survival for non-progressive processes

We discuss the estimation of the expected value of the quality-adjusted survival, based on multistate models. We generalize an earlier work, considering the sojourn times in health states are not identically distributed, for a given vector of covariates. Approaches based on semiparametric and parametric (exponential and Weibull distributions) methodologies are considered. A simulation study is conducted to evaluate the performance of the proposed estimator and the jackknife resampling method is used to estimate the variance of such estimator. An application to a real data set is also included.

On estimation and influence diagnostics for the Grubbs` model under heavy-tailed distributions

The Grubbs` measurement model is frequently used to compare several measuring devices. It is common to assume that the random terms have a normal distribution. However, such assumption makes the inference vulnerable to outlying observations, whereas scale mixtures of normal distributions have been an interesting alternative to produce robust estimates, keeping the elegancy and simplicity of the maximum likelihood theory. The aim of this paper is to develop an EM-type algorithm for the parameter estimation, and to use the local influence method to assess the robustness aspects of these parameter estimates under some usual perturbation schemes, In order to identify outliers and to criticize the model building we use the local influence procedure in a Study to compare the precision of several thermocouples. (C) 2008 Elsevier B.V. All rights reserved.

Systematic risk estimation in symmetric models

The aim of this article is to discuss the estimation of the systematic risk in capital asset pricing models with heavy-tailed error distributions to explain the asset returns. Diagnostic methods for assessing departures from the model assumptions as well as the influence of observations on the parameter estimates are also presented. It may be shown that outlying observations are down weighted in the maximum likelihood equations of linear models with heavy-tailed error distributions, such as Student-t, power exponential, logistic II, so on. This robustness aspect may also be extended to influential observations. An application in which the systematic risk estimate of Microsoft is compared under normal and heavy-tailed errors is presented for illustration.

Bayesian density estimation using Skew Student-t-Normal mixtures

We present a Bayesian approach for modeling heterogeneous data and estimate multimodal densities using mixtures of Skew Student-t-Normal distributions [Gomez, H.W., Venegas, O., Bolfarine, H., 2007. Skew-symmetric distributions generated by the distribution function of the normal distribution. Environmetrics 18, 395-407]. A stochastic representation that is useful for implementing a MCMC-type algorithm and results about existence of posterior moments are obtained. Marginal likelihood approximations are obtained, in order to compare mixture models with different number of component densities. Data sets concerning the Gross Domestic Product per capita (Human Development Report) and body mass index (National Health and Nutrition Examination Survey), previously studied in the related literature, are analyzed. (c) 2008 Elsevier B.V. All rights reserved.

Estimation of the mean quality-adjusted survival using a multistate model for the sojourn times

In clinical trials, it may be of interest taking into account physical and emotional well-being in addition to survival when comparing treatments. Quality-adjusted survival time has the advantage of incorporating information about both survival time and quality-of-life. In this paper, we discuss the estimation of the expected value of the quality-adjusted survival, based on multistate models for the sojourn times in health states. Semiparametric and parametric (with exponential distribution) approaches are considered. A simulation study is presented to evaluate the performance of the proposed estimator and the jackknife resampling method is used to compute bias and variance of the estimator. (C) 2007 Elsevier B.V. All rights reserved.

Improved maximum-likelihood estimation in a regression model with general parametrization

We analyse the finite-sample behaviour of two second-order bias-corrected alternatives to the maximum-likelihood estimator of the parameters in a multivariate normal regression model with general parametrization proposed by Patriota and Lemonte [A. G. Patriota and A. J. Lemonte, Bias correction in a multivariate regression model with genereal parameterization, Stat. Prob. Lett. 79 (2009), pp. 1655-1662]. The two finite-sample corrections we consider are the conventional second-order bias-corrected estimator and the bootstrap bias correction. We present the numerical results comparing the performance of these estimators. Our results reveal that analytical bias correction outperforms numerical bias corrections obtained from bootstrapping schemes.

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.

Sequential injection analysis (SIA) and response surface methodology: A versatile small volume approach for optimization of photo-Fenton processes

Optimization of photo-Fenton degradation of copper phthalocyanine blue was achieved by response surface methodology (RSM) constructed with the aid of a sequential injection analysis (SIA) system coupled to a homemade photo-reactor. Highest degradation percentage was obtained at the following conditions [H(2)O(2)]/[phthalocyanine] = 7, [H(2)O(2)]/[FeSO(4)] = 10, pH = 2.5, and stopped flow time in the photo reactor = 30 s. The SIA system was designed to prepare a monosegment containing the reagents and sample, to pump it toward the photo-reactor for the specified time and send the products to a flow-through spectrophotometer for monitoring the color reduction of the dye. Changes in parameters such as reagent molar ratios. residence time and pH were made by modifications in the software commanding the SI system, without the need for physical reconfiguration of reagents around the selection valve. The proposed procedure and system fed the statistical program with degradation data for fast construction of response surface plots. After optimization, 97% of the dye was degraded. (C) 2009 Elsevier B.V. All rights reserved.

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.

Development of a sequential injection chromatography (SIC) method for determination of simazine, atrazine, and propazine

This paper describes the development of a sequential injection chromatography (SIC) procedure for separation and quantification of the herbicides simazine, atrazine, and propazine exploring the low backpressure of a 2.5 cm long monolithic C(18) column. The separation of the three compounds was achieved in less than 90 s with resolution > 1.5 using a mobile phase composed by ACN/1.25 mmol/L acetate buffer (pH 4.5) at the volumetric ratio of 35:65 and flow rate of 40 mu L/s. Detection was made at 223 nm using a flow cell with 40 mm of optical path length. The LOD was 10 mu g/L for the three triazines and the quantification limits were of 30 mu g/L for simazine and propazine and 40 mu g/L for atrazine. The sampling frequency is 27 samples per hour, consuming 1.1 mL of ACN per analysis. The proposed methodology was applied to spiked water samples and no statistically significant differences were observed in comparison to a conventional HPLC-UV method. The major metabolites of atrazine and other herbicides did not interfere in the analysis, being eluted from the column either together with the unretained peak, or at retention times well-resolved from the studied compounds.

Applying sequential injection analysis (SIA) and response surface methodology for optimization of Fenton-based processes

This work presents the use of sequential injection analysis (SIA) and the response surface methodology as a tool for optimization of Fenton-based processes. Alizarin red S dye (C.I. 58005) was used as a model compound for the anthraquinones family. whose pigments have a large use in coatings industry. The following factors were considered: [H(2)O(2)]:[Alizarin] and [H(2)O(2)]:[FeSO(4)] ratios and pH. The SIA system was designed to add reagents to the reactor and to perform on-line sampling of the reaction medium, sending the samples to a flow-through spectrophotometer for monitoring the color reduction of the dye. The proposed system fed the statistical program with degradation data for fast construction of response surface plots. After optimization, 99.7% of the dye was degraded and the TOC content was reduced to 35% of the original value. Low reagents consumption and high sampling throughput were the remarkable features of the SIA system. (C) 2008 Published by Elsevier B.V.

Implementing stepwise solvent elution in sequential injection chromatography for fluorimetric determination of intracellular free amino acids in the microalgae Tetraselmis gracilis

The concept of sequential injection chromatography (SIC) was exploited to automate the fluorimetric determination of amino acids after pre-column derivatization with ophthaldialdehyde (OPA) in presence of 2-mercaptoethanol (2MCE) using a reverse phase monolithic C(18) stationary phase. The method is low-priced and based on five steps of isocratic elutions. The first step employs the mixture methanol: tetrahydrofuran: 10 mmol L(-1) phosphate buffer (pH 7.2) at the volumetric ratio of 8:1:91; the other steps use methanol: 10 mmol L-1 phosphate buffer (pH 7.2) at volumetric ratios of 20:80, 35:65, SO:SO and 65:35. At a flow rate of 10 mu L s(-1) a 25 mm long-column was able to separate aspartic acid (Asp), glutamic acid (Glu), asparagine (Asn), serine (Ser), glutamine (Gln), glycine (Gly), threonine (Thr), citruline (Ctr), arginine (Arg), alanine (Ala), tyrosine (Tyr), phenylalanine (Phe), ornithine (Orn) and lysine (Lys) with resolution >1.2 as well as methionine (Met) and valine (Val) with resolution of 0.6. Under these conditions isoleucine (Ile) and leucine (Leu) co-eluted. The entire cycle of amino acids derivatization, chromatographic separation and column conditioning at the end of separation lasted 25 min. At a flow rate of 40 mu L s(-1) such time was reduced to 10 min at the cost of resolution worsening for the pairs Ctr/Arg and Orn/Lys. The detection limits varied from 0.092 mu mol L(-1) for Tyr to 0.51 mu mol L(-1) for Orn. The method was successfully applied to the determination of intracellular free amino acids in the green alga Tetraselmis gracilis during a period of seven days of cultivation. Samples spiked with known amounts of amino acids resulted in recoveries between 94 and 112%. (C) 2008 Elsevier B.V. All rights reserved.