Covariance structure analysis in several populations

This paper is concerned with the study of covariance structural models in several populations. Estimation theory of the parameters that are subject to general functional restraints is developed based on the generalized least squares approach. Asymptotic properties of the constrained estimator are studied; and asymptotic chi-square tests are presented to evaluate appropriate model comparisons. The method of multipliers and the standard reparametrization technique are discussed in obtaining the estimates. The methodology is demonstrated by a set of real data.Computer facilities were provided by the Computer Services Center, The Chinese University of Hong Kong. The authors are indebted to several anonymous reviewers for suggestions for improvement of this paper.     

Two simple classes of mastery scores based on the beta-binomial model

Two simple classes of mastery scores which are suitable for hand calculations are presented for beta-binomial test score distributions combined with linear and cubic referral success. The models provide a simple way to explore the consequences of selecting an arbitrary mastery score. Such assessment would be useful whenever the test user is not willing to posta priori a loss ratio, but wishes to look at the various consequences before aiming at a particular score.     

Stopping rules for multi-category computerized classification testing

Computerized classification testing (CCT) aims to classify persons into one of two or more possible categories to make decisions such as mastery/non-mastery or meet most/meet all/exceed. A defining feature of CCT is its stopping criterion: the test terminates when there is enough confidence to make a decision. There is abundant research on CCT with a single cut-off, and two common stopping criteria are the sequential probability ratio test (SPRT) statistic and the generalized likelihood ratio statistic (GLR). However, there is a relative scarcity of research extending the SPRT to the multi-hypothesis case for when there is more than one cut-off. In this paper, we propose a new multi-category GLR (mGLR) statistic as well as a stochastically curtailed version of the CCT with three or more categories. A simulation study was conducted to show that the mGLR statistic outperformed the existing stopping rules by generating shorter average test length without sacrificing classification accuracy. Results also revealed that the stochastically curtailed mGLR successfully increased test efficiency in certain testing conditions.     

Recommandations de l’ITC pour la traduction et l’adaptation de tests (seconde édition)

The second edition of the ITC guidelines for translating and adapting tests was prepared between 2005 and 2015 to improve upon the first edition, and to respond to advances in testing technology and practices. The 18 guidelines are organized into six categories to facilitate their use: pre-condition (3), test development (5), confirmation (4), administration (2), scoring and interpretation (2), and documentation (2). For each guideline, an explanation is provided along with suggestions for practice. A checklist is provided to improve the implementation of the guidelines.     

输入方式对学语前聋生语篇理解的影响：文本和测题类型的调节效应

为了考察信息输入方式、文本类型和测题类型对聋生语篇理解的影响,研究通过录像呈现,以口语、手语、书面语三种输入方式向学语前极重度七、八、九年级聋生呈现叙述性和描述性两种文本类型的语篇信息,并要求其完成理解测试。结果显示：输入方式对聋生语篇理解的效率存在影响,书面语成绩最高且速度最快,依次为手语、口语,文本类型和测题类型对该影响有调节作用。结果表明输入方式是聋生语篇理解的主要影响因素,文本和测题类型是调节因素。     

Defensive reactions of “wild-type” and “Domesticated” wild rats to approach and contact by a threat stimulus

Selective breeding of wild rats over many generations on the basis of low or high defensive threat and attack to human approach and contact has produced highly polarized “domesticated” and “wild-type” animals. Because the selection procedure selectively involves these two defense patterns, and these clearly differ in the two groups, it is of interest to determine if other, nonselected, defensive behaviors to threat stimuli also change. “Domesticated” and “wild-type” rats of the thirty-fifth generation were run in a fear defense test battery (F/DTB) to systematically evaluate defensive behaviors to a variety of present threat stimuli. “Domesticated” rats showed reduced avoidance and slower flight speed to an approaching experimenter, reduced jump/startle response to handelap and dorsal contact, less vocalization and boxing to vibrissae stimulation or to an anesthetized conspecific, and reduced defensiveness to an attempted pickup by the experimenter. These results indicate that selective bi-directional breeding for defensive threat and attack to human approach and contact produces group differences in a variety of defensive behaviors, and in defensiveness to stimuli other than those on which the selection was based. © 1994 Wiley-Liss, Inc.     

Testing two variances for superiority/non-inferiority and equivalence: Using the exhaustion algorithm for sample size allocation with cost

The equality of two group variances is frequently tested in experiments. However, criticisms of null hypothesis statistical testing on means have recently arisen and there is interest in other types of statistical tests of hypotheses, such as superiority/non-inferiority and equivalence. Although these tests have become more common in psychology and social sciences, the corresponding sample size estimation for these tests is rarely discussed, especially when the sampling unit costs are unequal or group sizes are unequal for two groups. Thus, for finding optimal sample size, the present study derived an initial allocation by approximating the percentiles of an F distribution with the percentiles of the standard normal distribution and used the exhaustion algorithm to select the best combination of group sizes, thereby ensuring the resulting power reaches the designated level and is maximal with a minimal total cost. In this manner, optimization of sample size planning is achieved. The proposed sample size determination has a wide range of applications and is efficient in terms of Type I errors and statistical power in simulations. Finally, an illustrative example from a report by the Health Survey for England, 1995–1997, is presented using hypertension data. For ease of application, four R Shiny apps are provided and benchmarks for setting equivalence margins are suggested.     

On normal theory based inference for multilevel models with distributional violations

Data in social and behavioral sciences are often hierarchically organized though seldom normal, yet normal theory based inference procedures are routinely used for analyzing multilevel models. Based on this observation, simple adjustments to normal theory based results are proposed to minimize the consequences of violating normality assumptions. For characterizing the distribution of parameter estimates, sandwich-type covariance matrices are derived. Standard errors based on these covariance matrices remain consistent under distributional violations. Implications of various covariance estimators are also discussed. For evaluating the quality of a multilevel model, a rescaled statistic is given for both the hierarchical linear model and the hierarchical structural equation model. The rescaled statistic, improving the likelihood ratio statistic by estimating one extra parameter, approaches the same mean as its reference distribution. A simulation study with a 2-level factor model implies that the rescaled statistic is preferable.This research was supported by grants DA01070 and DA00017 from the National Institute on Drug Abuse and a University of North Texas faculty research grant. We would like to thank the Associate Editor and two reviewers for suggestions that helped to improve the paper.