A widely applicable extension of the random effects two-way layout: Its definition and statistical analysis based on group invariance

A type of data layout that may be considered as an extension of the two-way random effects analysis of variance is characterized and modeled based on group invariance. The data layout seems to be suitable for several scenarios in psychometrics, including the one in which multiple measurements are taken on each of a set of variables, and the measurements can be divided into exchangeable subsets. The algebraic structure of the model is studied, which leads to results that are applicable to such problems as estimating correlation matrix corrected for attenuation and testing symmetry hypotheses.The author would like to thank NIH for support through grants M01 RR00044 and P01 DE13539, and NSF and ASA Survey Section for a travel grant which allowed him to present this paper as an invited young researcher at the Conference in Celebration of Wayne A. Fuller's 70th birthday.     

FOK研究中一种新的标准测验——过度重复学习

提出FOK研究中一种新的标准测验形式——过度重复学习,并验证过度重复学习作为FOK研究的标准测验的可行性;另外还比较了作为标准测验,过度重复学习与再认的差别。同时,还探索了FOK判断中存在的两种错误类型——替代性错误和忽略性错误在FOK判断等级和标准测验成绩方面的差异。两个实验结果表明：FOK判断在预期随后的标准测验(过度重复学习和再认)成绩上是有准确性的;过度重复学习可以作为一种标准测验。实验结果还显示：替代性错误比忽略性错误的FOK判断等级要高;且无论是用再认还是用过度重复学习做标准测验,都能检验出两种错误类型项目在记忆激活强度上的差异。     

Prediction Errors and Attention in the Presence and Absence of Feedback

ABSTRACT— Contemporary theories of learning typically assume that learning is driven by prediction errors—in other words, that we learn more when our predictions turn out to be incorrect than we do when our predictions are correct. Results from the recording of electrical brain activity suggest one mechanism by which this might happen; we seem to direct visual attention toward the likely causes of previous prediction errors. This can happen very rapidly—within less than 200 milliseconds of the error-causing object being presented. It is tempting to infer that if learning is driven by prediction errors, then little can be learned in the absence of feedback. Such a conclusion is unwarranted. In fact, the substantial learning that is sometimes the result of simple exposure to objects can also be explained by processes of directing attention toward the likely causes of previous prediction errors.     

A primer on the understanding of meta-analysis

ObjectivesThe purpose of the present paper is to provide a primer on the understanding of meta-analysis.Design and methodAfter presenting the rationale behind meta-analysis, the present paper defines statistical artifacts of sampling error and measurement.FindingsExamples show that statistical artifacts influence the correlation coefficient. The paper also explains the notions of confidence intervals and credibility intervals and how correlations corrected for sampling error and measurement error are calculated.ConclusionsThe paper concludes by explaining the notion of second-order sampling error and moderator meta-analysis.     

INTRODUCTION TO THE SYMPOSIUM

This paper introduces a symposium discussing Michael Oakeshott's understanding of the relationship of religion, science and politics. Essays by Elizabeth Corey, Timothy Fuller, Byron Kaldis, and Corey Abel are followed by a review of Corey's recent book by Efraim Podoksik.     

大脑前扣带回皮层与执行功能

回顾了近期有关大脑前扣带回皮层（ACC）参与执行功能的研究资料。结果显示,ACC可以对正在进行的目标定向行为实施在线监控,在出现反应冲突或错误时提供信号,以便能及时调整与分配注意资源,因此可能是一个行为规划与执行的高级调控结构。这两年来的新发现提示,ACC的执行监控作用可能是基于动机与奖赏期待做出的对“意志行动”的整合性控制,并可能具有对行动结果的情绪评价意义。     

Using automation to combat the replication crisis: A case study from controlled-rearing studies of newborn chicks

The accuracy of science depends on the precision of its methods. When fields produce precise measurements, the scientific method can generate remarkable gains in knowledge. When fields produce noisy measurements, however, the scientific method is not guaranteed to work – in fact, noisy measurements are now regarded as a leading cause of the replication crisis in psychology. Scientists should therefore strive to improve the precision of their methods, especially in fields with noisy measurements. Here, we show that automation can reduce measurement error by ∼60% in one domain of developmental psychology: controlled-rearing studies of newborn chicks. Automated studies produce measurements that are 3–4 times more precise than non-automated studies and produce effect sizes that are 3–4 times larger than non-automated studies. Automation also eliminates experimenter bias and allows replications to be performed quickly and easily. We suggest that automation can be a powerful tool for improving measurement precision, producing high powered experiments, and combating the replication crisis.     

Improving Migrant Students' Spelling of English and Spanish Words with Error Correction

We examined the effects of error correction on spelling accuracy of culturally and linguistically diverse students enrolled in summer Migrant Education. In an error correction strategy, students spelled a word, viewed a correct model, and corrected specific errors. In a traditional strategy, students wrote words three times each while viewing a correct model. Words were presented in Spanish or English. Results showed that students with and without learning disabilities, whose primary language was English, correctly spelled more English words in the error correction condition than the traditional. Students whose primary language was Spanish correctly spelled Spanish words equally well in both conditions, possibly because of the phonetic nature of the Spanish language.     

A bayesian procedure for mastery decisions based on multivariate normal test data

A Bayesian framework for making mastery/nonmastery decisions based on multivariate test data is described in this study. Overall, mastery is granted (or denied) if the posterior expected loss associated with such action is smaller than the one incurred by the denial (or grant) of mastery. An explicit form for the cutting contour which separates mastery and nonmastery states in the test score space is given for multivariate normal test scores and for a constant loss ratio. For multiple cutting scores in the true ability space, the test score cutting contour will resemble the boundary defined by multiple test cutting scores when the test reliabilities are reasonably close to unity. For tests with low reliabilities, decisions may very well be based simply on a suitably chosen composite score.This work was performed pursuant to Grant NIE-G-78-0087 with the National Institute of Education, Department of Health, Education, and Welfare, Huynh Huynh, Principal Investigator. Points of view or opinions stated do not necessarily reflect NIE positions or policy and no official endorsement should be inferred. The assistance of Joseph C. Saunders is gratefully acknowledged. The author is indebted to an anonymous referee who pointed out several computational errors in the earlier versions of the paper.     

A model for repeat paired comparison preference tests

A model is proposed that describes subject behavior on repeat paired comparison preference tests. The model extends prior work in this area in that it explicitly allows for abstentions and permits the derivation of individual true scores for discrimination ability as well as conditional estimates of proportionate preference. With these results, the properties of a paired comparison test can be thoroughly explored. An empirical example is presented, and test design issues are considered. In particular, repeat paired comparison preference tests are shown to be inherently less efficient discrimination tests than are pick 1 of 2 tests.