On the analysis of studies of choice

In a review of 103 sets of data from 23 different studies of choice, Baum (1979) concluded that whereas undermatching was most commonly observed for responses, the time measure generally conformed to the matching relation. A reexamination of the evidence presented by Baum concludes that undermatching is the most commonly observed finding for both measures. Use of the coefficient of determination by both Baum (1979) and de Villiers (1977) for assessing when matching occurs is criticized on statistical grounds. An alternative to the loss-in-predictability criterion used by Baum (1979) is proposed. This alternative statistic has a simple operational meaning and is related to the usual F-ratio test. It can therefore be used as a formal test of the hypothesis that matching occurs. Baum (1979) also suggests that slope values of between .90 and 1.11 can be considered good approximations to matching. It is argued that the establishment of a fixed interval as a criterion for determining when matching occurs, is inappropriate. A confidence interval based on the data from any given experiment is suggested as a more useful method of assessment.     

证据顺序和证词自信度对学前末期儿童因果推理的影响

开展两个实验探究证据顺序和证词自信水平对5岁儿童因果推理的影响机制。132名和127名5岁儿童分别参与实验1和实验2。实验1发现证据顺序对儿童因果推理的影响表现为近因效应,但证词的自信水平差异不影响儿童的因果推理;实验2发现如果儿童注意到证词的自信水平信息,他们更倾向于在自信证词条件依据证词推断因果关系,证据顺序的影响力被削弱。研究结果说明证据顺序变化导致易受影响的近因效应。     

Effects of public feedback during RTI team meetings on teacher implementation integrity and student academic performance

As a result of the new revision of IDEA (2004), models of early intervention and response-to-intervention (RTI) have received a great deal of attention in the literature. Although various tiered models have been described in detail, one aspect of RTI that has received little empirical attention is the need to ensure integrity of intervention as part of a team decision making process. One method that has good support for improving treatment integrity is performance feedback (PFB); however, the utilization of PFB within a team context has received very little attention in the literature. Experiment 1 evaluated the effect of PFB delivered within the context of an RTI team on treatment integrity after fidelity had fallen to unacceptable levels. Experiment 2 evaluated the effects of PFB on the maintenance of treatment integrity prior to integrity fall off. Results indicate that PFB can be used as an efficient means of improving or maintaining treatment integrity when applied within a team model.     

归纳推理多样性效应的发展及其争论

归纳推理多样性效应指的是在归纳论断中,前提项目数量越多、越多样,将能构成归纳力度越强的推理。已有研究表明成人的归纳推理明显受到前提项目多样性的影响,而幼儿的相关研究却存在着两种对立的观点：一是认为幼儿不能基于多样性进行推理,二是认为5岁左右的幼儿就能够基于多样性进行推理。出现此争论的原因可能与研究方法方面的差异有关,如实验范式与前提组间差异、实验材料类别与概念范畴、属性特征及呈现方式、推理形式;此外,儿童的知识经验也是一个影响因素。未来研究可以结合相关领域的研究范式;深入挖掘影响儿童表现出多样性效应的因素;将任务设计多样化;将实验任务的计分方式多样化;开展相关的应用研究。     

初中生师生关系与主观幸福感的关系研究

目的：探讨初中生的师生关系与主观幸福感的关系。方法：对来自湖北省黄石市某中学300名学生进行主观幸福感量表和师生关系量表测试。结果：1、初中生的总体幸福感普遍偏低。2、初中生的师生关系存在显著性年级差异。初一学生要优于初二、初三学生。3、师生关系各因子与初中生主观幸福感各因子之间存在显著负相关（师生关系采用反向计分）。结论：初中生师生关系与主观幸福感密切相关。     

Confidently Biased: Comparisons with Anchors Bias Estimates and Increase Confidence

Across a wide variety of situations, exposure to anchors has been shown to bias people's estimates. What is not known, however, is whether externally provided anchors influence the confidence that people have in their estimates. Our studies had two goals. First, we tested whether exposure to anchors influenced people's subjective confidence levels (Studies 1 and 2). These studies revealed that people who made estimates after making comparisons with externally provided anchors tended to be more confident in their estimates than people who did not see anchors. The second goal was to test two explanations as to why anchors increase people's confidence. In Study 3, we tested the explanation that anchors increase confidence because participants thought the anchors provided useful information. In Study 4, we tested the explanation that exposure to anchors causes people to consider a narrower range of plausible values as compared to when not exposed to anchors. Support was found only for the explanation that comparisons with anchors increase confidence because people who are exposed to anchors consider a narrower range of plausible values. Taken together, these studies reveal the powerful influence anchors can have—they not only bias estimates, but also increase people's confidence in their biased estimates. Copyright © 2016 John Wiley & Sons, Ltd.     

Probabilities Associated with Precise and Vague Forecasts

Forecasts of future outcomes, such as the consequences of climate change, are given with different degrees of precision. Logically, more precise forecasts (e.g., a temperature increase of 3–4°) have a smaller probability of capturing the actual outcome than less precise forecasts (e.g., a temperature increase of 2–6°). Nevertheless, people often trust precise forecasts more than vague forecasts, perhaps because precision is associated with knowledge and expertise. In five experiments, we ask whether people expect highly confident forecasts to be associated with wider or narrower outcome ranges than less confident forecasts (Experiments 1, 2, and 5), and, conversely, whether they expect precise forecasts to be issued with higher or lower confidence than vague forecasts (Experiments 3 and 4). The results revealed two distinct ways of thinking about confidence intervals, labeled distributional (wide intervals seen as more probable than narrow intervals) and associative (wide intervals seen as more uncertain than narrow intervals). Distributional responses occurred somewhat more often in within‐subjects designs, where wide and narrow prediction intervals and high and low probability estimates can be directly compared, whereas separate evaluations (in between‐subjects design) suggested associative responses to be slightly more frequent. These findings are relevant for experts communicating forecasts through confidence intervals. Copyright © 2017 John Wiley & Sons, Ltd.     

Are you sure about that? Eliciting confidence ratings may influence performance on Raven's progressive matrices

Confidence ratings (CR) have often been integrated into reasoning and intelligence tasks as a means for assessing meta-reasoning processes. Although it is often assumed that eliciting these judgements throughout reasoning tasks has no effect on the underlying performance outcomes, this is yet to be established empirically. The current study examines whether eliciting CR from participants during a fluid-reasoning task influences their performance and how this effect is moderated by their initial self-confidence in their own reasoning abilities. In a first experiment, we found that participants performing CR during Raven's Progressive Matrices significantly outperformed a control group who did not provide ratings. Additionally, a second experiment demonstrated that CR only facilitated performance in participants who have a high level of initial self-confidence in their reasoning ability, whereas they were detrimental to participants low in self-confidence.     

The elimination‐plus lineup: Testing a modified lineup procedure with confidence

The present study examined whether a modified form of a preidentification confidence rating would provide evidence of a suspect's guilt in addition to the identification decision confidence. Participants (N  = 241) viewed a videotaped mock crime and were presented with a target‐present or target‐absent simultaneous, sequential, elimination, or elimination‐plus lineup procedure; both elimination procedures required 2 separate judgments from the witness (i.e., relative and absolute). The elimination‐plus procedure was identical to that of the elimination procedure with the addition of the confidence rating in between judgment 1 and judgment 2. Confidence after judgment 1, confidence after judgment 2, and the average of the 2 confidence ratings with the elimination‐plus procedure significantly predicted accuracy for choosers. Given that confidence has been recognised by the Supreme Court of the United States, these results shed light on a novel way of utilising confidence in the investigative process.     

Profile-likelihood Confidence Intervals in Item Response Theory Models

Confidence intervals (CIs) are fundamental inferential devices which quantify the sampling variability of parameter estimates. In item response theory, CIs have been primarily obtained from large-sample Wald-type approaches based on standard error estimates, derived from the observed or expected information matrix, after parameters have been estimated via maximum likelihood. An alternative approach to constructing CIs is to quantify sampling variability directly from the likelihood function with a technique known as profile-likelihood confidence intervals (PL CIs). In this article, we introduce PL CIs for item response theory models, compare PL CIs to classical large-sample Wald-type CIs, and demonstrate important distinctions among these CIs. CIs are then constructed for parameters directly estimated in the specified model and for transformed parameters which are often obtained post-estimation. Monte Carlo simulation results suggest that PL CIs perform consistently better than Wald-type CIs for both non-transformed and transformed parameters.