Group Cancellation and Resolution

We establish a connection between the geometric methods developed in the combinatorial theory of small cancellation and the propositional resolution calculus. We define a precise correspondence between resolution proofs in logic and diagrams in small cancellation theory, and as a consequence, we derive that a resolution proof is a 2-dimensional process. The isoperimetric function defined on diagrams corresponds to the length of resolution proofs.     

Accept Yourself! A Pilot Randomized Controlled Trial of a Self-Acceptance-Based Treatment for Large-Bodied Women With Depression

A pilot parallel randomized controlled trial compared a self-acceptance, non-weight-loss intervention, Accept Yourself! (AY), to a weight loss program, Weight Watchers (WW), in order to provide preliminary safety, feasibility, and efficacy data in preparation for a definitive RCT of AY as an intervention to enhance the mental and physical health of larger-bodied women with Major Depressive Disorder (MDD). Adult women with MDD and a Body Mass Index ≥30 were eligible. Nineteen women were randomized by random number table into AY (n = 9) or WW (n = 10). Intake, pretreatment, posttreatment, 3-, 6-, 9-, and 12-month follow-up assessments occurred at a rural academic medical center. Primary outcomes included depression severity and cardiovascular fitness. Chi-square and t-tests assessed attrition and participant preferences for treatment; other analyses used intention-to-treat, linear mixed-effects models for repeated measures, including all participants’ available data. Both groups improved in self-reported, F(5, 43.81) = 7.45, p < .001, partial η² = .38, and blinded-clinician-rated depression, F(6, 62.03) = 10.41, p < .001, partial η² = .5. AY was superior to WW in self-reported depression, F(5, 43.81) = 2.72, p = .03, partial η² = .11. Neither group improved in fitness. Eating disorder symptoms and weight gain worsened in WW. AY appeared safe, feasible, and offered initial evidence of efficacy for depression; it should be investigated in a definitive RCT, with modifications to increase potency. WW may not be suitable as a comparator intervention for AY because of risk to participants.     

Dysfunctional implications of narrow window theory: variability in the intuitive assessment of correlation

Narrow Window theory, suggested by Y. Kareev ten years ago, has so far focused on one central implication of the limited capacity of working memory on intuitive correlation estimation, namely, overestimation of the distal population correlation. This paper points to additional and perhaps more dramatic implications due to the large dispersion of intuitive estimates: (a) large estimation errors, possibly causing overestimation of negligible rhos, misses of strong rhos, and distorted hierarchies of the rhos between different pairs of variables; and (b) large interpersonal differences in the estimation of any given rho and highly incongruent hierarchies of estimated correlations between different pairs of variables. These implications impede both individuals' adaptation to the empirical world and communication among themselves.     

A derived transfer of functions and the implicit association test

Participants were trained in a series of interrelated conditional discriminations that aimed to establish four 4-member equivalence classes (i.e., A1-B1-C1-D1, A2-B2-C2-D2, A3-B3-C3-D3, A4-B4-C4-D4). During this training, the four A stimuli (i.e., A1, A2, A3, and A4) were compounded with pictures containing positive or negative evaluative functions (A1/A2 negative & A3/A4 positive). The transfer of evaluative functions to directly and indirectly related members of the equivalence classes (i.e., B, C, and D stimuli) was measured using an Implicit Association Test (IAT). During consistent test blocks, participants were required to press the same response key for target words that were related to those A stimuli that possessed similar evaluative functions (A1/A2-left key & A3/A4-right key). During inconsistent test blocks, target words that were related to those A stimuli with different evaluative functions were assigned to the same response key (A1/A4-left key & A2/A3-right key). Results showed that all 8 participants, who passed a matching-to-sample equivalence test following the IAT, responded more rapidly on consistent relative to inconsistent test blocks. This typical IAT effect was not observed for those participants who did not pass the equivalence test. The results suggest that the IAT effect may arise from formally untested derived relations, and supports the argument that such relations could provide a valid behavioral model of semantic categories in natural language.     

群体过程与互动分析系统

群体过程由各种行动和行为反应组成,具有动态性和复杂性。以往研究根据群体均衡理论、功能观点或时间理论等分别开发了各种基于研究者视角的群体互动过程观察分析系统。但很多研究结论并不一致,主要原因在于各个分析系统的关注点不同。本研究从信效度、理论基础、分析对象以及编码难易等角度总结了各个系统的优点和不足,并进一步提出未来研究可能的方向：构建适当的群体决策动态实验任务、明确群体过程作用机制、以及开发运用于实践的群体互动过程分析系统。     

非小细胞肺癌靶向药物治疗争论热点

非小细胞肺癌作为全球和我国发病率最高、死亡人数最多的恶性肿瘤,其药物治疗始终是临床肿瘤学界高度关注的焦点之一。肿瘤的药物治疗模式从单纯以细胞毒药物杀伤肿瘤逐步向调节信号传导通路转变,分子靶向药物日益成为治疗肿瘤的重要武器。回顾肺癌靶向治疗的进展,诸多问题需要解决。     

Use of samples differing markedly in salience may encourage use of a single-code/default strategy in matching-to-sample in pigeons

To test the hypothesis that pigeons will only code the more salient sample when samples differ markedly in salience, pigeons were trained with samples consisting of a 2-s presentation of food (highly salient sample) and an 8-s presentation of keylight (less salient sample). During retention testing, pigeons tended to respond at longer delays as if an 8-s keylight sample had been presented. This finding is consistent with use of a single-code/default strategy in which only the 2-s food sample was coded and the comparison associated with an 8-s keylight sample was selected by default in the absence of memory for the salient 2-s food sample. Hence, a marked difference in sample salience appears to encourage use of a single-code/default strategy.     

Single and double alternation learning in rats: The role of set size and correction

In many experiments, rats have evidenced extreme difficulty mastering alternation patterns. In three experiments, we explored rats’ ability to learn double alternation patterns and possible reasons behind their past difficulties with such patterns. In Experiment 1, rats learned single and double alternation patterns. In the second and third experiment, we explored the role of correction and interference from stimulus set size on rats’ learning of double alternation patterns. Our results showed that rats easily learned both single and double alternation patterns and that stimulus set size had no noticeable effect on learning double alternation patterns. Findings additionally evidenced that correction played an important role in rats’ learning double alternation patterns.     

Identifying Variables Responsible for Data not Missing at Random

When data are not missing at random (NMAR), maximum likelihood (ML) procedure will not generate consistent parameter estimates unless the missing data mechanism is correctly modeled. Understanding NMAR mechanism in a data set would allow one to better use the ML methodology. A survey or questionnaire may contain many items; certain items may be responsible for NMAR values in other items. The paper develops statistical procedures to identify the responsible items. By comparing ML estimates (MLE), statistics are developed to test whether the MLEs are changed when excluding items. The items that cause a significant change of the MLEs are responsible for the NMAR mechanism. Normal distribution is used for obtaining the MLEs; a sandwich-type covariance matrix is used to account for distribution violations. The class of nonnormal distributions within which the procedure is valid is provided. Both saturated and structural models are considered. Effect sizes are also defined and studied. The results indicate that more missing data in a sample does not necessarily imply more significant test statistics due to smaller effect sizes. Knowing the true population means and covariances or the parameter values in structural equation models may not make things easier either. The research was supported by NSF grant DMS04-37167, the James McKeen Cattell Fund.