The authors assessed the impact of three designs (randomized experiment, nonequivalent control group design, regression discontinuity design) on estimates of effect size of a university-level freshman remedial writing program. Designs were implemented within the same context, same time frame, and with the same population. The 375 freshman participants were either randomly assigned or self-selected into specific evaluation groups, according to design protocols. The three designs led to highly similar effect size estimates of the impact of a semester of remedial writing on writing outcomes following standard freshman composition. Specific design features contributed to the convergence of effect size estimates across designs.The purposes of this research are both methodological and substantive. From a methodological perspective, we compare effect size estimates resulting from the implementation of a randomized experiment versus two different

Bayesian methods are theoretically optimal in many situations. Bayesian model averaging is generally considered the standard model for creating ensembles of learners using Bayesian methods, but this technique is often outperformed by more ad hoc methods in empirical studies. The reason for this failure has important theoretical implications for our understanding of why ensembles work. It has been proposed that Bayesian model averaging struggles in practice because it accounts for uncertainty about which model is correct but still operates under the assumption that only one of them is. In order to more effectively access the benefits inherent in ensembles, Bayesian strategies should therefore be directed more towards model combination rather than the model selection implicit in Bayesian model averaging. This work provides empirical verification for this hypothesis using several different Bayesian model combination approaches tested on a wide variety of classification problems. We show that even the most simplistic of Bayesian model combination strategies outperforms the traditional ad hoc techniques of bagging and boosting, as well as outperforming BMA over a wide variety of cases. This suggests that the power of ensembles does not come from their ability to account for model uncertainty, but instead comes from the changes in representational and preferential bias inherent in the process of combining several different models.

This study addresses the adult romantic attachment styles of sexually addicted men. The Sexual Addiction Screening Test and the Experiences in Close Relationships Revised were used to determine the presence of a sexual addiction and the participants' style of romantic attachment. ANOVA revealed that sexually addicted men are more likely to relate with insecure attachment styles. Specifically, sexually addicted men were found to have

Neuregulin-1 (NRG-1), binding to the human epidermal growth factor receptor HER2/HER3, plays a role in pulmonary epithelial cell proliferation and recovery from injury in vitro. We hypothesized that activation of HER2/HER3 by NRG-1 would also play a role in recovery from in vivo lung injury. We tested this hypothesis using bleomycin lung injury of transgenic mice incapable of signaling through HER2/HER3 due to lung-specific dominant-negative HER3 (DNHER3) expression. In animals expressing DNHER3, protein leak, cell infiltration, and NRG-1 levels in bronchoalveolar lavage fluid increased after injury, similar to that in nontransgenic littermate control animals. However, HER2/HER3 was not activated, and DNHER3 animals displayed fewer lung morphological changes at 10 and 21 days after injury (P = 0.01). In addition, they contained 51% less collagen in injured lungs (P = 0.04). Transforming growth factor-beta1 did not increase in bronchoalveolar lavage fluid from DNHER3 mice compared with nontransgenic littermate mice (P = 0.001), suggesting that a mechanism for the decreased fibrosis was lack of transforming growth factor-beta1 induction in DNHER3 mice. Severe lung injury (0.08 units bleomycin) resulted in 80% mortality of nontransgenic mice, but only 35% mortality of DNHER3 transgenic mice (P = 0.04). Thus inhibition of HER2/HER3 signaling protects against pulmonary fibrosis and improves survival.

Recent research in task transfer and task clustering has necessitated the need for task similarity measures in reinforcement learning. Determining task similarity is necessary for selective transfer where only information from relevant tasks and portions of a task are transferred. Which task similarity measure to use is not immediately obvious. It can be shown that no single task similarity measure is uniformly superior. The optimal task similarity measure is dependent upon the task transfer method being employed. We define similarity in terms of tasks, and propose several possible task similarity measures, dT, dp, dQ, and dR which are based on the transfer time, policy overlap, Q-values, and reward structure respectively. We evaluate their performance in three separate experimental situations.