Conditional Covariance Theory and Detect for Polytomous Items

This paper extends the theory of conditional covariances to polytomous items. It has been proven that under some mild conditions, commonly assumed in the analysis of response data, the conditional covariance of two items, dichotomously or polytomously scored, given an appropriately chosen composite is positive if, and only if, the two items measure similar constructs besides the composite. The theory provides a theoretical foundation for dimensionality assessment procedures based on conditional covariances or correlations, such as DETECT and DIMTEST, so that the performance of these procedures is theoretically justified when applied to response data with polytomous items. Various estimators of conditional covariances are constructed, and special attention is paid to the case of complex sampling data, such as those from the National Assessment of Educational Progress (NAEP). As such, the new version of DETECT can be applied to response data sets not only with polytomous items but also with missing values, either by design or at random. DETECT is then applied to analyze the dimensional structure of the 2002 NAEP reading samples of grades 4 and 8. The DETECT results show that the substantive test structure based on the purposes for reading is consistent with the statistical dimensional structure for either grade. This research was supported by the Educational Testing Service and the National Assessment of Educational Progress (Grant R902F980001), US Department of Education. The opinions expressed herein are solely those of the author and do not necessarily represent those of the Educational Testing Service. The author would like to thank Ting Lu, Paul Holland, Shelby Haberman, and Feng Yu for their comments and suggestions. Requests for reprints should be sent to Jinming Zhang, Educational Testing Service, MS 02-T, Rosedale Road, Princeton, NJ 08541, USA. E-mail: jzhang@ets.org     

A general Bayesian multilevel multidimensional IRT model for locally dependent data

Many item response theory (IRT) models take a multidimensional perspective to deal with sources that induce local item dependence (LID), with these models often making an orthogonal assumption about the dimensional structure of the data. One reason for this assumption is because of the indeterminacy issue in estimating the correlations among the dimensions in structures often specified to deal with sources of LID (e.g., bifactor and two-tier structures), and the assumption usually goes untested. Unfortunately, the mere fact that assessing these correlations is a challenge for some estimation methods does not mean that data seen in practice support such orthogonal structure. In this paper, a Bayesian multilevel multidimensional IRT model for locally dependent data is presented. This model can test whether item response data violate the orthogonal assumption that many IRT models make about the dimensional structure of the data when addressing sources of LID, and this test is carried out at the dimensional level while accounting for sampling clusters. Simulations show that the model presented is effective at carrying out this task. The utility of the model is also illustrated on an empirical data set.     

Cognitive organization of disease concepts in Singapore

Abstract

This research investigates illness cognition and its relationship to the use of different types of medicine in three ethnic groups in Singapore. Four hundred and twenty-nine Chinese, Malay, and Indian Singaporeans rated 24 diseases as to their similarity. Multidimensional scaling (MDS) indicated three dimensions. Regression of these dimensions against 17 disease attributes suggested that these dimensions represented spiritual/psychological causation, disease severity, and viral causation. When the dimensions were related to the use of, preference for and perceived effectiveness of different types of medicine it was found that Indian medicine tended to be used, preferred and perceived to be most effective for diseases low in severity whereas Chinese medicine was viewed most favourably for diseases perceived to be low in spiritual/psychological causation as well as those not seen as virally caused. Malay medicine tended to used, preferred and perceived as most effective for conditions believed to be non-serious and not caused by a virus. Western medicine was most likely to be used, preferred, and seen as most effective for diseases viewed as serious as well as those believed to be virally caused.     

Estimating Optimal Weights for Compound Scores: A Multidimensional IRT Approach

A method is proposed for constructing indices as linear functions of variables such that the reliability of the compound score is maximized. Reliability is defined in the framework of latent variable modeling [i.e., item response theory (IRT)] and optimal weights of the components of the index are found by maximizing the posterior variance relative to the total latent variable variance. Three methods for estimating the weights are proposed. The first is a likelihood-based approach, that is, marginal maximum likelihood (MML). The other two are Bayesian approaches based on Markov chain Monte Carlo (MCMC) computational methods. One is based on an augmented Gibbs sampler specifically targeted at IRT, and the other is based on a general purpose Gibbs sampler such as implemented in OpenBugs and Jags. Simulation studies are presented to demonstrate the procedure and to compare the three methods. Results are very similar, so practitioners may be suggested the use of the easily accessible latter method. A real-data set pertaining to the 28-joint Disease Activity Score is used to show how the methods can be applied in a complex measurement situation with multiple time points and mixed data formats.     

The Future of the Church as a Primary Health Place

ABSTRACT

There is a critical need for change in America's Health System, and religious organizations can facilitate not only the redefining of what health is but also the shaping of what the primary health services of the future should look like, function as, and be. The vision presented here is that the local parish or some extension of it be seen by the average citizen as a primary health place. The model proposed is that faith based living in community become the core health concept, defining what it means to be human and healthy become the core teaching, and that healing such that no illness need dominate become the goal. Within that context, health information, education, prayer, care, and support for most chronic illness, lifestyle change, and end of life concerns would begin at one's community of faith and only within that context to specially trained persons. This health system will compliment the sophisticated and complex acute medical care system that now exists.     

Competitive state anxiety and self-confidence: Intensity and direction as relative predictors of performance on a golf putting task

Abstract

This study considered relationships between the intensity and directional aspects of competitive state anxiety as measured by the modified Competitive Sport Anxiety Inventory-2(D) (Jones & Swain, 1992 Jones, G. and Swain, A. B. J. 1992. Intensity and direction as dimensions of competitive state anxiety and relationships with competitiveness. Perceptual and Motor Skills, 74: 467–472. [Crossref], [PubMed], [Web of Science ®] , [Google Scholar]) in a sample of 12 experienced male golfers. Anxiety and performance scores from identical putting tasks performed under three different anxiety-manipulated competitive conditions were used to assess both the predictions of Multidimensional Anxiety Theory (MAT; Martens et al., 1990 Martens, R., Burton, D., Vealey, R., Bump, L. and Smith, D. 1990. “The development of the Competitive State Anxiety Inventory-2 (CSAI-2)”. In Competitive anxiety in sport, Edited by: Martens, R., Vealey, R. S. and Burton, D. 117–190. Champaign, IL: Human Kinetics.  [Google Scholar]) and the relative value of intensity and direction in explaining performance variance. A within-subjects regression analysis of the intra-individual data showed partial support for the three MAT hypotheses. Cognitive anxiety intensity demonstrated a negative linear relationship with performance, somatic anxiety intensity showed a curvilinear relationship with performance, and self-confidence intensity revealed a positive linear relation. Cognitive directional anxiety illustrated a positive linear relationship with putting performance. Multiple regression analyses indicated that direction (42% of variance) was a better predictor of performance than intensity (22%)     

人格测量：从累积式模型到展开式模型

当前大多数人格测量都采用的是累积式反应模型方法,该模型假设被试在测验上的得分随其能力或特质提高而增加,但是随着人格测量技术的不断发展,这一模型的实施效果遭到了质疑,研究者们开始关注展开式模型,该模型认为被试的反应取决于被试能力和项目阈值的匹配程度,当被试能力与项目阈值完全匹配时,被试做出肯定回答的概率达到最高点,称之为“理想点”,展开式模型的目的就是找到被试的理想点,从而寻找其真正的态度强度或人格特质水平。GGUM作为一种比较成熟的展开式模型,已经开始应用于人格测量的各个领域,但仍需要进行大规模的试测,在评估和预测效度方面积累经验,建立业界认可的心理测量学标准,不断探讨和开发相应的心理测量理论和简便易行的统计程序。     

DNA研究的历史带给我们的启示

自然科学发展日新月异。墨守成规的传统思维模式常常是羁绊研究工作停滞不前的主要障碍。通过纵观DNA双螺旋结构的研究历程,认识到实事求是的态度是确立正确研究方向的基础,而全方位、多视角、多学科交叉的开放性思维模式给科学研究带来了更宽阔的途径。     

当代大学生自比型价值观数据的潜在结构

本研究对采自3796名在校大学生的Rokeach Value Survey自比型数据进行了因素分析和多维尺度分析。因素分析从两组价值观选项中分别获得6个双极因素,虽然内容各不相同,但均体现出个人指向-亲社会指向的特点。多维尺度分析所获得的两组选项的2维空间距离分布结果也体现类似特点,结果显示终极性价值观可分为四类,工具性价值观可分为五类。当前大学生价值观中存在着舒适的物质生活、兴奋的生活、幸福、快乐和自尊以及雄心壮志的、勇敢的和诚实的等个人取向内容占优势的可能性。在两种分析方法中,多维尺度分析更适合对自比型价值观数据潜在结构的探究。     

A latent trait model for dichotomous choice data

The PARELLA model is a probabilistic parallelogram model that can be used for the measurement of latent attitudes or latent preferences. The data analyzed are the dichotomous responses of persons to stimuli, with a one (zero) indicating agreement (disagreement) with the content of the stimulus. The model provides a unidimensional representation of persons and items. The response probabilities are a function of the distance between person and stimulus: the smaller the distance, the larger the probability that a person will agree with the content of the stimulus. An estimation procedure based on expectation maximization and marginal maximum likelihood is developed and the quality of the resulting parameter estimates evaluated.I gratefully acknowledge Ivo Molenaar and Wijbrandt van Schuur for their advice and encouragement during the course of the investigation, Derk-Jan Kiewiet who constructed the program for the ML estimator for the person parameter and Anne Boomsma, Wendy Post, Tom Snijders, and David Thissen for their comments on smaller aspects of the investigation.