EMERGENT CONDITIONAL RELATIONS IN A GO/NO-GO PROCEDURE: FIGURE-GROUND AND STIMULUS-POSITION COMPOUND RELATIONS

Past research has demonstrated emergent conditional relations using a go/no-go procedure with pairs of figures displayed side-by-side on a computer screen. The present Study sought to extend applications Of this procedure. In Experiment, 1, we evaluated whether emergent conditional relations Could be demonstrated when two-component stimuli were displayed in figure-ground relationships-abstract figures displayed on backgrounds of different colors. Five normal)), capable adults participated. During training, each two-component stimulus Was presented successively. Responses emitted in the presence of some Stimulus pairs (A1B1, A2B2, A3B3, B1C1, B2C2 and B3C3) were reinforced, whereas responses emitted in the presence of other pairs (A1B2, A1B3, A2B1, A2B3, A3B1, A3B2, B1C2, B1C3, B2C1, B2C3, B3C1 and B3C2) were not. During tests, new configurations (AC and CA) were presented, thus emulating structurally the matching-to-sample tests employed in typical equivalence Studies. All participants showed emergent relations consistent with stimulus equivalence during testing. In Experiment 2, we systematically replicated the procedures with Stimulus compounds consisting Of four figures (A1, A2, C1 and C2) and two locations (left - B1 and right - 132). A,11 6 normally capable adults exhibited emergent stimulus-stimulus relations. Together, these experiments show that the go/no-go procedure is a potentially useful alternative for Studying emergent. conditional relations when matching-to-sample is procedurally cumbersome or impossible to use.

The impact of the Bolsa Escola/Familia conditional cash transfer program on enrollment, dropout rates and grade promotion in Brazil

We examine the impact of Brazil's Bolsa Escola/Familia program on Brazilian children's education outcomes. Bolsa provides cash payments to poor households if their children (ages 6 to 15) are enrolled in school. Using school census data to compare changes in enrollment, dropping out and grade promotion across schools that adopted Bolsa at different times, we estimate that the program has: increased enrollment by about 5.5% (6.5%) in grades 1-4 (grades 5-8); lowered dropout rates by 0.5 (0.4) percentage points in grades 1-4 (grades 5-8); and raised grade promotion rates by 0.9 (0.3) percentage points in grades 1-4 (grades 5-8). About one third of Brazil's children participate in Bolsa, so assuming no spillover effects onto non-participants implies that Bolsa's impacts are three times higher than these estimates. However, simple calculations using enrollment impacts suggest that Bolsa's benefits in terms of increased wages may not exceed its costs. (C) 2011 Elsevier B.V. All rights reserved.

Bivariate gamma-geometric law and its induced Levy process

In this article we introduce a three-parameter extension of the bivariate exponential-geometric (BEG) law (Kozubowski and Panorska, 2005) [4]. We refer to this new distribution as the bivariate gamma-geometric (BGG) law. A bivariate random vector (X, N) follows the BGG law if N has geometric distribution and X may be represented (in law) as a sum of N independent and identically distributed gamma variables, where these variables are independent of N. Statistical properties such as moment generation and characteristic functions, moments and a variance-covariance matrix are provided. The marginal and conditional laws are also studied. We show that BBG distribution is infinitely divisible, just as the BEG model is. Further, we provide alternative representations for the BGG distribution and show that it enjoys a geometric stability property. Maximum likelihood estimation and inference are discussed and a reparametrization is proposed in order to obtain orthogonality of the parameters. We present an application to a real data set where our model provides a better fit than the BEG model. Our bivariate distribution induces a bivariate Levy process with correlated gamma and negative binomial processes, which extends the bivariate Levy motion proposed by Kozubowski et al. (2008) [6]. The marginals of our Levy motion are a mixture of gamma and negative binomial processes and we named it BMixGNB motion. Basic properties such as stochastic self-similarity and the covariance matrix of the process are presented. The bivariate distribution at fixed time of our BMixGNB process is also studied and some results are derived, including a discussion about maximum likelihood estimation and inference. (C) 2012 Elsevier Inc. All rights reserved.

Computational tools for comparing asymmetric GARCH models via Bayes factors

In this paper we use Markov chain Monte Carlo (MCMC) methods in order to estimate and compare GARCH models from a Bayesian perspective. We allow for possibly heavy tailed and asymmetric distributions in the error term. We use a general method proposed in the literature to introduce skewness into a continuous unimodal and symmetric distribution. For each model we compute an approximation to the marginal likelihood, based on the MCMC output. From these approximations we compute Bayes factors and posterior model probabilities. (C) 2012 IMACS. Published by Elsevier B.V. All rights reserved.

A General Latent Class Model for Performance Evaluation of Diagnostic Tests in the Absence of a Gold Standard: An Application to Chagas Disease

We propose a new general Bayesian latent class model for evaluation of the performance of multiple diagnostic tests in situations in which no gold standard test exists based on a computationally intensive approach. The modeling represents an interesting and suitable alternative to models with complex structures that involve the general case of several conditionally independent diagnostic tests, covariates, and strata with different disease prevalences. The technique of stratifying the population according to different disease prevalence rates does not add further marked complexity to the modeling, but it makes the model more flexible and interpretable. To illustrate the general model proposed, we evaluate the performance of six diagnostic screening tests for Chagas disease considering some epidemiological variables. Serology at the time of donation (negative, positive, inconclusive) was considered as a factor of stratification in the model. The general model with stratification of the population performed better in comparison with its concurrents without stratification. The group formed by the testing laboratory Biomanguinhos FIOCRUZ-kit (c-ELISA and rec-ELISA) is the best option in the confirmation process by presenting false-negative rate of 0.0002% from the serial scheme. We are 100% sure that the donor is healthy when these two tests have negative results and he is chagasic when they have positive results.

Do pets reduce the likelihood of sudden unexplained death in epilepsy?

Purpose: To assess the relationship between the presence of pets in homes of epilepsy patients and the occurrence of sudden unexpected death in epilepsy (SUDEP). Methods: Parents or relatives of SUDEP patients collected over a ten-year period (2000-2009) in a large epilepsy unit were asked if the patient lived together with any domestic pet at the time of death or not. Patients who did not experience SUDEP served as controls. Results and conclusions: Eleven out of the 1092 included patients (1%) experienced SUDEP, all with refractory symptomatic epilepsy, but none of them had pets in their homes at the time of death. In contrast, the frequency of pet-ownership in the control group (n = 1081) was 61%. According to previous studies there are some indications that human health is directly related to companionship with animals in a way that domestic animals prevent illness and facilitate recovery of patients. Companion animals can buffer reactivity against acute stress, diminish stress perception and improve physical health. These factors may reduce cardiac arrhythmias and seizure frequency, factors related to SUDEP. Companion animals may have a positive effect on well-being, thus irnproving epilepsy outcome. (c) 2012 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.

Aging reduces complexity of heart rate variability assessed by conditional entropy and symbolic analysis

Increasing age is associated with a reduction in overall heart rate variability as well as changes in complexity of physiologic dynamics. The aim of this study was to verify if the alterations in autonomic modulation of heart rate caused by the aging process could be detected by Shannon entropy (SE), conditional entropy (CE) and symbolic analysis (SA). Complexity analysis was carried out in 44 healthy subjects divided into two groups: old (n = 23, 63 +/- A 3 years) and young group (n = 21, 23 +/- A 2). It was analyzed SE, CE [complexity index (CI) and normalized CI (NCI)] and SA (0V, 1V, 2LV and 2ULV patterns) during short heart period series (200 cardiac beats) derived from ECG recordings during 15 min of rest in a supine position. The sequences characterized by three heart periods with no significant variations (0V), and that with two significant unlike variations (2ULV) reflect changes in sympathetic and vagal modulation, respectively. The unpaired t test (or Mann-Whitney rank sum test when appropriate) was used in the statistical analysis. In the aging process, the distributions of patterns (SE) remain similar to young subjects. However, the regularity is significantly different; the patterns are more repetitive in the old group (a decrease of CI and NCI). The amounts of pattern types are different: 0V is increased and 2LV and 2ULV are reduced in the old group. These differences indicate marked change of autonomic regulation. The CE and SA are feasible techniques to detect alteration in autonomic control of heart rate in the old group.

Likelihood-based inference for power distributions

This paper considers likelihood-based inference for the family of power distributions. Widely applicable results are presented which can be used to conduct inference for all three parameters of the general location-scale extension of the family. More specific results are given for the special case of the power normal model. The analysis of a large data set, formed from density measurements for a certain type of pollen, illustrates the application of the family and the results for likelihood-based inference. Throughout, comparisons are made with analogous results for the direct parametrisation of the skew-normal distribution.