MSA for a special spearman matrix

Kaiser's measure of sampling adequacy is applied to a special Spearman matrix and a specialq-cluster generalization. The result supports the contention that the measure should be no less than .5 for data to be appropriate for factor analysis.The research reported in this note was supported in part by the Program in Applied Mathematics and Statistics, National Science Foundation, and by the National Institute of Education, Department of Health, Education, and Welfare.     

认知诊断模型Q矩阵修正：完整信息矩阵的作用

Q矩阵是CDM的核心元素之一,反映了测验的内部结构和内容设计,通常由领域专家根据经验进行主观界定,因此需要对可能存在的错误进行修正。本研究提出了一种新的Q矩阵修正方法——基于完整经验交叉相乘信息矩阵的Wald-XPD方法。采用Monte Carlo模拟检验了新方法的表现,并与同类方法进行了比较。研究表明：新开发的Wald-XPD方法在Q矩阵恢复率、保留正确标定属性的比例以及修正错误标定属性的比例这3个主要指标上均有较好的表现,且整体上优于其他方法,尤其是在修正错误标定的属性方面。通过实证数据展示了Wald-XPD方法在Q矩阵修正中的良好表现。总之,本研究为Q矩阵修正提供了有效的方法。     

Sentence comprehension and production in children with cochlear implants: Errorless procedures and equivalence-based instruction

Research supports equivalence-based instruction (EBI) and matrix training for increased listening and speaking skills in children with cochlear implants (CI). We incorporated errorless procedures to optimize the EBI and evaluated the effects on the auditory comprehension and verbal responding at-sentences level in six CI children who were readers and showed inaccurate tacting. Subject-verb-object sentences were arranged in two matrices; diagonal combinations were trained and evaluated non-diagonal combinations. EBI included stimulus fading and exclusion to directly teach the dictated sentence-picture matching; written-sentences construction upon dictation also was taught. Probes assessed the derived stimulus-stimulus and stimulus-response relations. All participants learned the auditory-visual discriminations and the exclusion resulted in fewer errors than on a stimulus fading procedure. Five participants formed equivalence classes and increased verbal responding to equivalent stimuli, especially pictures tacting. They also showed recombinative generalization for both matrices. Professionals can incorporate errorless procedures to EBI for improving sentence comprehension, tacting, and productivity in CI children.     

Compact integer-programming models for extracting subsets of stimuli from confusion matrices

This paper presents an integer linear programming formulation for the problem of extracting a subset of stimuli from a confusion matrix. The objective is to select stimuli such that total confusion among the stimuli is minimized for a particular subset size. This formulation provides a drastic reduction in the number of variables and constraints relative to a previously proposed formulation for the same problem. An extension of the formulation is provided for a biobjective problem that considers both confusion and recognition in the objective function. Demonstrations using an empirical interletter confusion matrix from the psychological literature revealed that a commercial branch-and-bound integer programming code was always able to identify optimal solutions for both the single-objective and biobjective formulations within a matter of seconds. A further extension and demonstration of the model is provided for the extraction of multiple subsets of stimuli, wherein the objectives are to maximize similarity within subsets and minimize similarity between subsets.     

An evaluation of matrix training to teach college students piano notes and rhythms

Twelve college students learned to tact the names of notes and rhythms and play them when presented with compound stimuli (visuals of notes and rhythms on a musical staff). In Experiment 1, we assessed generalization by presenting novel notes, rhythms, and compound stimuli not previously paired together. In the second experiment, we added a metronome that played at 60 beats per minute in all conditions for 3 out of 6 participants to ensure consistent tempo. Across both experiments, participants passed almost all posttests with the exception of tacting and playing in the presence of sound clips. Our data suggest that matrix training is an effective procedure to teach music skills to college students.     

哪个测验Q矩阵更合理:基于DINA模型测验Q矩阵合理性侦查指标及其比较与应用

本研究对多个测验Q矩阵的相对合理性的比较与选用开展研究,采用Monte Carlo模拟与实证研究相结合的范式,探讨R_square、HCI、-2LL、AIC、BIC、residual、ABS_residual及本研究新开发的BIC2等八项指标在测验Q矩阵合理性侦查效果及其比较。研究发现:八项指标中,除BIC和BIC2两项指标的对测验Q矩阵相对合理性的平均正确识别率在95%以上,其余指标的平均正确识别率不足90%,整体而言,考虑样本容量及参数个数双重加权的BIC和BIC2两项指标的表现总体上优于其它几项指标;各项指标在不同Q矩阵错误类型下其正确识别率也不尽相同。     

A Comparison of Inverse-Wishart Prior Specifications for Covariance Matrices in Multilevel Autoregressive Models

Multilevel autoregressive models are especially suited for modeling between-person differences in within-person processes. Fitting these models with Bayesian techniques requires the specification of prior distributions for all parameters. Often it is desirable to specify prior distributions that have negligible effects on the resulting parameter estimates. However, the conjugate prior distribution for covariance matrices—the Inverse-Wishart distribution—tends to be informative when variances are close to zero. This is problematic for multilevel autoregressive models, because autoregressive parameters are usually small for each individual, so that the variance of these parameters will be small. We performed a simulation study to compare the performance of three Inverse-Wishart prior specifications suggested in the literature, when one or more variances for the random effects in the multilevel autoregressive model are small. Our results show that the prior specification that uses plug-in ML estimates of the variances performs best. We advise to always include a sensitivity analysis for the prior specification for covariance matrices of random parameters, especially in autoregressive models, and to include a data-based prior specification in this analysis. We illustrate such an analysis by means of an empirical application on repeated measures data on worrying and positive affect.     

The Symptom as Ally,not Enemy

The practice of the Western medicine often identifies the symptom with the disease itself, but a current of thought and medical practice considers it as the important message of an organic imbalance. In fact, in standard therapies symptoms are usually suppressed, thus interrupting a normal physiological process and risking severe reactions due to the organic imbalance. Dr. Hahnemann, the father of homeopathy, founded his diagnostic and therapeutic model on the interpretation of the symptoms and maintained that symptoms are an expression of altered physiology. The same concept is to be found in Dr. Reckeweg's “reactivity” and homotoxicology; he believed that diseases are the expression of the struggle of the body against toxins. Reckeweg's contribution was particularly important in considering the inflammation process as a biologic process through which the body restores its health. Also PNEI (psycho-neuro-endocrino-immunology) proposes a model where the symptom is interpreted as information and as the result of an imbalance. Several other medical approaches address particular attention to the meaning of symptoms. The Bach Flower Therapy, for instance, is guided exclusively by the negative moods, which can become the cause of functional and organic diseases; balance is restored thanks to superior harmonic energetic vibrations conveyed by the superior energy living in some flowers. This interpretation of the nature of symptoms is becoming a more and more relevant issue among both the specialistic and the general public.     

On initial item selection in cognitive diagnostic computerized adaptive testing

There has recently been much interest in computerized adaptive testing (CAT) for cognitive diagnosis. While there exist various item selection criteria and different asymptotically optimal designs, these are mostly constructed based on the asymptotic theory assuming the test length goes to infinity. In practice, with limited test lengths, the desired asymptotic optimality may not always apply, and there are few studies in the literature concerning the optimal design of finite items. Related questions, such as how many items we need in order to be able to identify the attribute pattern of an examinee and what types of initial items provide the optimal classification results, are still open. This paper aims to answer these questions by providing non‐asymptotic theory of the optimal selection of initial items in cognitive diagnostic CAT. In particular, for the optimal design, we provide necessary and sufficient conditions for the Q ‐matrix structure of the initial items. The theoretical development is suitable for a general family of cognitive diagnostic models. The results not only provide a guideline for the design of optimal item selection procedures, but also may be applied to guide item bank construction.     

题库结构对原始题在线属性标定准确性之影响研究

目前已有研究证明可达阵在认知诊断测验编制中起重要作用,但迄今为止并没有引起普遍注意。本文主要讨论当题库缺少某些可达阵对应的项目类,对原始题的属性向量在线标定的准确性的影响。本文对含6个属性的独立型结构进行了模拟试验,结果显示：如果题库不充要,原始题的属性标定准确性受到影响,题库中非可达阵中项目对标定有一定的弥补作用。间接印证了可达阵在认知诊断题库起到非常重要的作用。