Parameter recovery for a skew-normal IRT model under a Bayesian approach: hierarchical framework, prior and kernel sensitivity and sample size

Item response theory (IRT) comprises a set of statistical models which are useful in many fields, especially when there is an interest in studying latent variables (or latent traits). Usually such latent traits are assumed to be random variables and a convenient distribution is assigned to them. A very common choice for such a distribution has been the standard normal. Recently, Azevedo et al. [Bayesian inference for a skew-normal IRT model under the centred parameterization, Comput. Stat. Data Anal. 55 (2011), pp. 353-365] proposed a skew-normal distribution under the centred parameterization (SNCP) as had been studied in [R. B. Arellano-Valle and A. Azzalini, The centred parametrization for the multivariate skew-normal distribution, J. Multivariate Anal. 99(7) (2008), pp. 1362-1382], to model the latent trait distribution. This approach allows one to represent any asymmetric behaviour concerning the latent trait distribution. Also, they developed a Metropolis-Hastings within the Gibbs sampling (MHWGS) algorithm based on the density of the SNCP. They showed that the algorithm recovers all parameters properly. Their results indicated that, in the presence of asymmetry, the proposed model and the estimation algorithm perform better than the usual model and estimation methods. Our main goal in this paper is to propose another type of MHWGS algorithm based on a stochastic representation (hierarchical structure) of the SNCP studied in [N. Henze, A probabilistic representation of the skew-normal distribution, Scand. J. Statist. 13 (1986), pp. 271-275]. Our algorithm has only one Metropolis-Hastings step, in opposition to the algorithm developed by Azevedo et al., which has two such steps. This not only makes the implementation easier but also reduces the number of proposal densities to be used, which can be a problem in the implementation of MHWGS algorithms, as can be seen in [R.J. Patz and B.W. Junker, A straightforward approach to Markov Chain Monte Carlo methods for item response models, J. Educ. Behav. Stat. 24(2) (1999), pp. 146-178; R. J. Patz and B. W. Junker, The applications and extensions of MCMC in IRT: Multiple item types, missing data, and rated responses, J. Educ. Behav. Stat. 24(4) (1999), pp. 342-366; A. Gelman, G.O. Roberts, and W.R. Gilks, Efficient Metropolis jumping rules, Bayesian Stat. 5 (1996), pp. 599-607]. Moreover, we consider a modified beta prior (which generalizes the one considered in [3]) and a Jeffreys prior for the asymmetry parameter. Furthermore, we study the sensitivity of such priors as well as the use of different kernel densities for this parameter. Finally, we assess the impact of the number of examinees, number of items and the asymmetry level on the parameter recovery. Results of the simulation study indicated that our approach performed equally as well as that in [3], in terms of parameter recovery, mainly using the Jeffreys prior. Also, they indicated that the asymmetry level has the highest impact on parameter recovery, even though it is relatively small. A real data analysis is considered jointly with the development of model fitting assessment tools. The results are compared with the ones obtained by Azevedo et al. The results indicate that using the hierarchical approach allows us to implement MCMC algorithms more easily, it facilitates diagnosis of the convergence and also it can be very useful to fit more complex skew IRT models.

Closed-loop stable model predictive control of integrating systems with dead time

Model predictive control (MPC) applications in the process industry usually deal with process systems that show time delays (dead times) between the system inputs and outputs. Also, in many industrial applications of MPC, integrating outputs resulting from liquid level control or recycle streams need to be considered as controlled outputs. Conventional MPC packages can be applied to time-delay systems but stability of the closed loop system will depend on the tuning parameters of the controller and cannot be guaranteed even in the nominal case. In this work, a state space model based on the analytical step response model is extended to the case of integrating time systems with time delays. This model is applied to the development of two versions of a nominally stable MPC, which is designed to the practical scenario in which one has targets for some of the inputs and/or outputs that may be unreachable and zone control (or interval tracking) for the remaining outputs. The controller is tested through simulation of a multivariable industrial reactor system. (C) 2012 Elsevier Ltd. All rights reserved.

A crucial role for IL-6 in the CNS of rats during fever induced by the injection of live E. coli

Interleukin (IL)-1 beta, tumor necrosis factor (TNF)-alpha, and IL-6 have been established as important mediators of fever induced by lipopolysaccharide (LPS) from Gram-negative bacteria. Whether these pro-inflammatory cytokines are also important in mediating fever induced by live bacteria remains less certain. We therefore investigated the following: (1) the synthesis of TNF-alpha, IL-1 beta, and IL-6 during E. coli-induced fever and (2) the effect of blocking the action of cytokines within the brain on E. coli-induced fever. Body or tail skin temperature (bT or Tsk, respectively) was measured by biotelemetry or telethermometry, every 30 min, during 6 or 24 h. Depending on the number of colony-forming units (CFU) injected i.p., administration of E. coli induced a long-lasting increase in bT of male Wistar rats. The duration of fever did not correlate with the number of CFU found in peritoneal cavity or blood. Because 2.5 x 10(8) CFU induced a sustained fever without inducing a state of sepsis/severe infection, this dose was used in subsequent experiments. The E. coli-induced increase in bT was preceded by a decrease in Tsk, reflecting a thermoregulatory response. TNF-alpha, IL-1 beta, and IL-6 were detected at 3 h in serum of animals injected i.p. with E. coli. In the peritoneal exudates, TNF-alpha, IL-1 beta, and IL-6 were detected at 0.5 and 3 h after E. coli administration. Moreover, both IL-1 beta and IL-6, but not TNF-alpha, were found in the cerebrospinal fluid (CSF) and hypothalamus of animals injected with E. coli. Although pre-treatment (i.c.v., 2 mu l, 15 min before) with anti-IL-6 antibody (anti-IL-6, 5 mu g) reduced E. coli-induced fever, pre-treatment with either IL-1 receptor antagonist (IL-1ra, 200 mu g) or soluble TNF receptor I (sTNFRI, 500 ng) had no effect on the fever response. In conclusion, replicating E. coli promotes an integrated thermoregulatory response in which the central action of IL-6, but not IL-1 and TNF, appears to be important.

Child Physical Abuse: Evaluating Psychological Risk Factors in Accused Caregivers

It was verified to what extent cognitive and affective/emotional variables could distinguish caregivers accused of committing physical abuse (G1) from those without physical abuse records (G2). The Child Abuse Potential Inventory (CAP), which is an instrument designed to assess psychological risk factors in caregivers, was used. A questionnaire on socio-demographic characterization and another on economic classification were also employed to equate the groups. G1 presented a greater potential risk than G2, higher levels of Distress, Rigidity, Problems with the Child and with Themselves, Problems with Others, and a lower level of Ego Strength. These variables contribute with the composition of physical abuse risk, since, in agreement with the Social Information Processing Model, they would be related to cognitive and affective basic processes which are veiled to the perceptions and evaluation/interpretations, associated to abusive parental behavior.

Abuso físico infantil: avaliando fatores de risco psicológicos em cuidadores notificados

Verificou-se em que medida variáveis cognitivas e afetivas/emocionais diferenciariam cuidadores notificados por abusos físicos (G1) de cuidadores sem esse histórico (G2). O Child Abuse Potential Inventory (CAP) foi utilizado para avaliar fatores de risco psicológicos em cuidadores. Um Questionário de Caracterização sócio-demográfica e outro econômico também foram empregados para equiparar os grupos. G1 apresentou um potencial de risco superior a G2, e maiores níveis de Angústia, Rigidez, Problemas com a Criança e Consigo, Problemas com os Outros, e um menor nível de Força do Ego. Essas variáveis se articulam para compor o risco de abuso físico, pois segundo o Modelo do Processamento da Informação Social, remeteriam a processos básicos cognitivos/afetivos subjacentes a percepções e avaliações/interpretações, associados ao comportamento parental abusivo.