Effect of instructed extinction on verbal and autonomic indices of Pavlovian learning with fear-relevant and fear-irrelevant conditional stimuli

We investigated the effects of conditional stimulus fear-relevance and of instructed extinction on human Pavlovian conditioning as indexed by electrodermal responses and verbal ratings of conditional stimulus unpleasantness. Half of the participants (n = 64) were trained with pictures of snakes and spiders (fear-relevant) as conditional stimuli, whereas the others were trained with pictures of flowers and mushrooms (fear-irrelevant) in a differential aversive Pavlovian conditioning procedure. Half of the participants in each group were instructed after the completion of acquisition that no more unconditional stimuli were to be presented. Extinction of differential electrodermal responses required more trials after training with fear-relevant pictures. Moreover, there was some evidence that verbal instructions did not affect extinction of second interval electrodermal responses to fear-relevant pictures. However, neither fear-relevance nor instructions affected the changes in rated conditional stimulus pleasantness. This dissociation across measures is interpreted as reflecting renewal of Pavlovian learning.

Conditional simulation of random fields by successive residuals

This paper presents a new approach to the LU decomposition method for the simulation of stationary and ergodic random fields. The approach overcomes the size limitations of LU and is suitable for any size simulation. The proposed approach can facilitate fast updating of generated realizations with new data, when appropriate, without repeating the full simulation process. Based on a novel column partitioning of the L matrix, expressed in terms of successive conditional covariance matrices, the approach presented here demonstrates that LU simulation is equivalent to the successive solution of kriging residual estimates plus random terms. Consequently, it can be used for the LU decomposition of matrices of any size. The simulation approach is termed conditional simulation by successive residuals as at each step, a small set (group) of random variables is simulated with a LU decomposition of a matrix of updated conditional covariance of residuals. The simulated group is then used to estimate residuals without the need to solve large systems of equations.

Knowledge of the national emergency telephone number and prevalence and characteristics of those trained in CPR in Queensland: baseline information for targeted training interventions

Members of the community contribute to survival from out-of-hospital cardiac arrest by contacting emergency medical services and performing cardiopulmonary resuscitation (CPR) prior to the arrival of an ambulance. In Australia there is a paucity of information of the extent that community members know the emergency telephone number and are trained in CPR. A survey of Queensland adults (n = 4490) was conducted to ascertain current knowledge and training levels and to target CPR training. Although most respondents (88.3%) could state the Australian emergency telephone number correctly, significant age differences were apparent (P < 0.001). One in five respondents aged 60 years and older could not state the emergency number correctly. While just over half the respondents (53.9%) had completed some form of CPR training, only 12.1% had recent training. Older people were more likely to have never had CPR training than young adults. Additional demographic and socio-economic differences were found between those never trained in CPR and those who were. The results emphasise the need to increase CPR training in those aged 40 and over, particularly females, and to increase the awareness of the emergency telephone number amongst older people. (C) 2002 Elsevier Science Ireland Ltd. All rights reserved.

An EM-based Semi-Parametric Mixture Model Approach to the Regression Analysis of Competing-Risks Data

We consider a mixture model approach to the regression analysis of competing-risks data. Attention is focused on inference concerning the effects of factors on both the probability of occurrence and the hazard rate conditional on each of the failure types. These two quantities are specified in the mixture model using the logistic model and the proportional hazards model, respectively. We propose a semi-parametric mixture method to estimate the logistic and regression coefficients jointly, whereby the component-baseline hazard functions are completely unspecified. Estimation is based on maximum likelihood on the basis of the full likelihood, implemented via an expectation-conditional maximization (ECM) algorithm. Simulation studies are performed to compare the performance of the proposed semi-parametric method with a fully parametric mixture approach. The results show that when the component-baseline hazard is monotonic increasing, the semi-parametric and fully parametric mixture approaches are comparable for mildly and moderately censored samples. When the component-baseline hazard is not monotonic increasing, the semi-parametric method consistently provides less biased estimates than a fully parametric approach and is comparable in efficiency in the estimation of the parameters for all levels of censoring. The methods are illustrated using a real data set of prostate cancer patients treated with different dosages of the drug diethylstilbestrol. Copyright (C) 2003 John Wiley Sons, Ltd.