Selecting the normal population with the smallest variance: A restricted subset selection rule

Consider k( ? 2) normal populations whose means are all known or unknown and whose variances are unknown. Let σ²_[1] ? ??? ? σ_[k]² denote the ordered variances. Our goal is to select a non empty subset of the k populations whose size is at most m(1 ? m ? k ? 1) so that the population associated with the smallest variance (called the best population) is included in the selected subset with a guaranteed minimum probability P* whenever σ²_[2]/σ_[1]² ? δ* > 1, where P* and δ* are specified in advance of the experiment. Based on samples of size n from each of the populations, we propose and investigate a procedure called R_BCP. We also derive some asymptotic results for our procedure. Some comparisons with an earlier available procedure are presented in terms of the average subset sizes for selected slippage configurations based on simulations. The results are illustrated by an example.     

Bayesian averaging of classical estimates in asymmetric vector autoregressive models

The estimated vector autoregressive (VAR) model is sensitive to model misspecifications, resulting to biased and inconsistent parameter estimates. This article extends the Bayesian averaging of classical estimates, a robustness procedure in cross-section data, to a vector time-series that is estimated using a large number of asymmetric VAR models. The proposed procedure was applied to simulated data from various forms of model misspecifications. The results of the simulation suggest that, under misspecification problems, particularly if an important variable and moving average (MA) terms were omitted, the proposed procedure gives robust results and better forecasts than the automatically selected equal lag-length VAR model.     

Bayesian Design of Special Type of Double Sampling Plans for Compliance Testing

Bayesian acceptance sampling plans, which utilize prior information on the process variation, can be employed as an alternative to conventional types of plans for taking decisions on the disposition of submitted lots. A special type of double sampling inspection plans by attributes with small acceptance numbers using Bayesian methodology is presented in this paper emphasizing its significance over small acceptance number single sampling plans. The procedures for designing such sampling plans for specified degree of discrimination which would ensure protection to the producer and consumer are discussed with illustrations under the conditions for the application of gamma-Poisson distribution.     

Empty Looks or Paying Attention? Exploring Infants' Visual Behavior during Encoding of an Elicited Imitation Task

Recently, there has been an increased interest in the relationship between looking time during encoding and subsequent memory performance in imitation tasks. Hitherto, the results have been inconclusive: one line of research supporting the link between looking time and performance and another line finding no relation. The existing studies may, however, have been restricted by using small samples, limited looking time measures, and short retention intervals. We here examined the relationship between the encoding process by means of looking time as well as pupil dilation (by means of eye‐tracking technology) in sixty‐eight 20‐month‐old infants participating in an elicited imitation task and their subsequent memory performance (at an encoding test and at a 2‐week delayed recall test). Additional twenty‐two infants provided baseline measures. Simple looking time (assessed as fixation duration) did not correlate consistently with subsequent memory measures. In some cases, however, looking time correlated negatively with imitation scores. In contrast, positive correlations were found between pupil dilation and some of the memory measures, suggesting that pupil dilation may be a more sensitive tool compared to looking time measures.     

Odd-Burr generalized family of distributions with some applications

We study a new family of continuous distributions with two extra shape parameters called the Burr generalized family of distributions. We investigate the shapes of the density and hazard rate function. We derive explicit expressions for some of its mathematical quantities. The estimation of the model parameters is performed by maximum likelihood. We prove the flexibility of the new family by means of applications to two real data sets. Furthermore, we propose a new extended regression model based on the logarithm of the Burr generalized distribution. This model can be very useful to the analysis of real data and provide more realistic fits than other special regression models.     

At 10–12 Months,Pointing Gesture Handedness Predicts the Size of Receptive Vocabularies

The close association between language and gesture has been widely studied (McNeill, Psychological Review, 92, 1985, 350). It remains unclear, however, when and how this relationship originates ontogenetically. This study investigated the relationship between vocabulary development and pointing handedness in 10‐ to 12‐month‐old infants. The study used cross‐sectional data from 16 infants. Infants took part in a pointing elicitation task and a grasping task to assess their pointing and grasping handedness. Further, parents filled out the Oxford Communicative Development Inventory (Hamilton, Plunkett, & Schafer, Journal of Child Language, 27, 2000, 689) to assess infants’ receptive and productive vocabularies. The result showed a positive, significant correlation between receptive vocabulary development and right‐handed pointing. This relationship was not due to age or to vocalizations, which have not been ruled out by previous studies. Possible mechanisms behind this codevelopment are discussed.     

A Bayesian approach for zero-modified Skellam model with Hamiltonian MCMC

Statistical Methods & Applications - In this paper is presented the zero-modified poisson difference and present possible applications of them in the analysis of paired count data. The...     

Does Hearing About Cancer Influence Stimulus Control? An Exploratory Study of Verbal Modulation of Stimulus Generalization

The Analysis of Verbal Behavior - Participants first became familiar with an image showing moderate symptoms of the skin cancer melanoma. In a generalization test, they indicated whether images...     

Making Professional Decisions in Research: Measurement and Key Predictors

The professional decision-making in research (PDR) measure was administered to 400 National Institutes of Health (NIH)-funded and industry-funded investigators, along with measures of cynicism, moral disengagement, compliance disengagement, impulsivity, work stressors, knowledge of responsible conduct of research (RCR), and socially desirable response tendencies. Negative associations were found for the PDR and measures of cynicism, moral disengagement, and compliance disengagement, while positive associations were found for the PDR and RCR knowledge and positive urgency, an impulsivity subscale. PDR scores were not related to socially desirable responding, or to measures of work stressors and the remaining impulsivity subscales. In a multivariate logistic regression analysis, lower moral disengagement scores, higher RCR knowledge, and identifying the United States as one’s nation of origin emerged as key predictors of stronger performance on the PDR. The implications of these findings for understanding the measurement of decision-making in research and future directions for research and RCR education are discussed.