Precision teaching's unique legacy from B. F. Skinner

Precision Teaching's unique legacy from B. F. Skinner was the monitoring system of rate of response and the cumulative response recorder. This legacy is unique because the other instructional systems derived from Skinner's work do not use his monitoring method exclusively. Rate of response, cumulative recording and their extension to Precision Teaching's standard celeration charting are briefly described. In addition, Precision Teaching's nature, history, costs, distribution, inductive data-base, and academic base are briefly described. Skinner's legacy to education was a sound behavioral scientific base and his unique legacy to Precision Teaching was self-monitoring for real time decision making by learners and teachers.     

A feasible method for standard errors of estimate in maximum likelihood factor analysis

A jackknife-like procedure is developed for producing standard errors of estimate in maximum likelihood factor analysis. Unlike earlier methods based on information theory, the procedure developed is computationally feasible on larger problems. Unlike earlier methods based on the jackknife, the present procedure is not plagued by the factor alignment problem, the Heywood case problem, or the necessity to jackknife by groups. Standard errors may be produced for rotated and unrotated loading estimates using either orthogonal or oblique rotation as well as for estimates of unique factor variances and common factor correlations. The total cost for larger problems is a small multiple of the square of the number of variables times the number of observations used in the analysis. Examples are given to demonstrate the feasibility of the method.The research done by R. I. Jennrich was supported in part by NSF Grant MCS 77-02121. The research done by D. B. Clarkson was supported in part by NSERC Grant A3109.     

The Impossibility of Local Skepticism

According to global skepticism, we know nothing. According to local skepticism, we know nothing in some particular area or domain of discourse. Unlike their global counterparts, local skeptics think they can contain our invincible ignorance within limited bounds. I argue that they are mistaken. Local skepticism, particularly the kinds that most often get defended, cannot stay local: if there are domains whose truths we cannot know, then there must be claims outside those domains that we cannot know even if they are true. My argument focuses on one popular form of local skepticism, ethical skepticism, but I believe that the argument generalizes to cover other forms as well.

The definition of adequate care in externally sponsored clinical trials: The terminological controversy about the concept “standard of care”

The treatment of the control group in externally sponsored clinical trials is the issue of one of the most heated debates in international research ethics. The paradigmatic cases are the mother-to-child HIV-transmission trials that took place in 16 developing countries in 1997, where the control group received a placebo while proven treatment was available in industrialized countries. From this circumstance results the controversy as to whether the sponsor and researchers of externally sponsored trials have to supply a treatment that is usually not available in the host country. From the beginning of the debate the controversial level of treatment has been called “standard of care”. However, besides the disagreement about the quality of the care that has to be supplied, there is as yet no widely accepted clear meaning of this concept. This article examines the fundamental ambiguity of the term and its formal function as an ethical criterion including suggestions on its further use. This paper was presented at the 6th International Bioethics Conference on the subject of ‘The Responsible Conduct of Basic and Clinical Research’, held in Warsaw, Poland, 3–4 June 2005.     

On muthén’s maximum likelihood for two-level covariance structure models

Data in social and behavioral sciences are often hierarchically organized. Special statistical procedures that take into account the dependence of such observations have been developed. Among procedures for 2-level covariance structure analysis, Muthén’s maximum likelihood (MUML) has the advantage of easier computation and faster convergence. When data are balanced, MUML is equivalent to the maximum likelihood procedure. Simulation results in the literature endorse the MUML procedure also for unbalanced data. This paper studies the analytical properties of the MUML procedure in general. The results indicate that the MUML procedure leads to correct model inference asymptotically when level-2 sample size goes to infinity and the coefficient of variation of the level-1 sample sizes goes to zero. The study clearly identifies the impact of level-1 and level-2 sample sizes on the standard errors and test statistic of the MUML procedure. Analytical results explain previous simulation results and will guide the design or data collection for the future applications of MUML.This research was supported by NSF Grant DMS04-37167.We thank Dr.Bengt Muthén for providing key references. We are also grateful to three expert reviewers for their constructive comments that have led the paper to an improvement over the previous version.This revised article was published online in August 2005 with the PDF paginated correctly.     

A model-based approach to multivariate principal component regression: Selecting principal components and estimating standard errors for unstandardized regression coefficients

Principal component regression (PCR) is a popular technique in data analysis and machine learning. However, the technique has two limitations. First, the principal components (PCs) with the largest variances may not be relevant to the outcome variables. Second, the lack of standard error estimates for the unstandardized regression coefficients makes it hard to interpret the results. To address these two limitations, we propose a model-based approach that includes two mean and covariance structure models defined for multivariate PCR. By estimating the defined models, we can obtain inferential information that will allow us to test the explanatory power of individual PCs and compute the standard error estimates for the unstandardized regression coefficients. A real example is used to illustrate our approach, and simulation studies under normality and nonnormality conditions are presented to validate the standard error estimates for the unstandardized regression coefficients. Finally, future research topics are discussed.     

对三维心理旋转操作任务特性的效应的初步研究

在认知心理学领域,对心理旋转的研究主要是以反应时范式为基础。本研究试图突破反应时范式,把心理测量学和实验的方法相结合,以现代测量理论——项目反应理论的项目参数（如项目难度、区分度、猜测参数）为指标,对心理旋转测验中,操作任务的若干特性对测验项目特性的影响进行研究,结果发现：对于以Ｓｈｅｐａｒｄ三维旋转材料编制的心理旋转测验、测验材料的复杂程度,标准图形和匹配图形的角度差,以及匹配图形的编排位置等对测验项目的诸特性均无显著影响。     

Analysis of residuals for the multionmial item response model

Using the item response model as developed on the multinomial distribution, asymptotic variances are obtained for residuals associated with response patterns and first-, and second-order marginal frequencies of manifest variables. When the model does not fit well, an examination of these residuals may reveal the source of the poor fit. Finally, a limited-information test of fit for the model is developed by using residuals defined for the first-, and second-order marginals. Model evaluation based on residuals for these marginals is particularly useful when the response pattern frequencies are sparse.The author would like to thank Yasuo Amemiya and Joseph Lucke for helpful suggestions. This research was supported by a Research Incentive Grant from Arizona State University.     

A note on the asymptotic variance-covariance matrix of item parameter estimates in the rasch model

Lord and Wingersky have developed a method for computing the asymptotic variance-covariance matrix of maximum likelihood estimates for item and person parameters under some restrictions on the estimates which are needed in order to fix the latent scale. The method is tedious, but can be simplified for the Rasch model when one is only interested in the item parameters. This is demonstrated here under a suitable restriction on the item parameter estimates.     

An algorithm for generating artificial test clusters

An algorithm for generating artificial data sets which contain distinct nonoverlapping clusters is presented. The algorithm is useful for generating test data sets for Monte Carlo validation research conducted on clustering methods or statistics. The algorithm generates data sets which contain either 1, 2, 3, 4, or 5 clusters. By default, the data are embedded in either a 4, 6, or 8 dimensional space. Three different patterns for assigning the points to the clusters are provided. One pattern assigns the points equally to the clusters while the remaining two schemes produce clusters of unequal sizes. Finally, a number of methods for introducing error in the data have been incorporated in the algorithm.