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.     

A unified approach to exploratory factor analysis with missing data,nonnormal data,and in the presence of outliers

Factor analysis is regularly used for analyzing survey data. Missing data, data with outliers and consequently nonnormal data are very common for data obtained through questionnaires. Based on covariance matrix estimates for such nonstandard samples, a unified approach for factor analysis is developed. By generalizing the approach of maximum likelihood under constraints, statistical properties of the estimates for factor loadings and error variances are obtained. A rescaled Bartlett-corrected statistic is proposed for evaluating the number of factors. Equivariance and invariance of parameter estimates and their standard errors for canonical, varimax, and normalized varimax rotations are discussed. Numerical results illustrate the sensitivity of classical methods and advantages of the proposed procedures.This project was supported by a University of North Texas Faculty Research Grant, Grant #R49/CCR610528 for Disease Control and Prevention from the National Center for Injury Prevention and Control, and Grant DA01070 from the National Institute on Drug Abuse. The results do not necessarily represent the official view of the funding agencies. The authors are grateful to three reviewers for suggestions that improved the presentation of this paper.     

Satisfiability Testing for Boolean Formulas Using Δ-trees

The tree-based data structure of -tree for propositional formulas is introduced in an improved and optimised form. The -trees allow a compact representation for negation normal forms as well as for a number of reduction strategies in order to consider only those occurrences of literals which are relevant for the satisfiability of the input formula. These reduction strategies are divided into two subsets (meaning- and satisfiability-preserving transformations) and can be used to decrease the size of a negation normal form A at (at most) quadratic cost. The reduction strategies are aimed at decreasing the number of required branchings and, therefore, these strategies allow to limit the size of the search space for the SAT problem.     

Beyond Speech Lateralization: A Review of the Variability, Reliability, and Validity of the Intracarotid Amobarbital Procedure and Its Nonlanguage Uses in Epilepsy Surgery Candidates

While the intracarotid amobarbital procedure (IAP) was originally utilized to lateralize speech functions as an aid in the surgical treatment of epilepsy, additional uses for the IAP have emerged including: (1) the use of the IAP to predict post-surgical memory changes, including both global amnesia and smaller, yet significant, material-specific memory deficits; (2) the use of the IAP to provide confirmatory evidence of lateralization of seizure focus; and (3) the use of the IAP to predict post-surgical relief from seizures. While the literature on the IAP is extensive and growing, its utility is marred by the wide variability associated with the procedure itself from epilepsy center to center. This variability renders comparisons among IAP studies problematic and conclusions about IAP efficacy difficult. The variability associated with the amobarbital procedures, as well as the reliability and the validity of the IAP in its nonlanguage uses is reviewed here. A special emphasis is devoted to research conducted in the last decade. Also discussed is the future of the IAP including anticipated research directions.     

From case management to prevention of scientific dishonesty in Denmark

In 1992, The Danish Medical Research Council established a national committee on scientific dishonesty with the twofold task of handling cases of scientific misconduct and taking preventive initiatives. Scientific dishonesty was proven in only five cases, but in another nine cases lesser degrees of deviations from good scientific practice were found. The experiences from a total of 24 treated cases indicated that three key areas were at the basis of most of the accusations and the deviations from good practice: uncertainty about 1) authorship, about 2) rights and duties to use scientific data and about 3) agreements at the initiation of joint studies. As a consequence guidelines on good practice have been issued on these key subjects. An earlier version of this paper was presented at a symposium, Scientific Misconduct. An International Perspective, organised by The Medical University of Warsaw, 16 November, 1998.     

The use of genetic test information in insurance: The argument from indistinguishability reconsidered

In the bioethical literature, discrimination in insurance on the basis of genetic risk factors detected by genetic testing has been defended and opposed on various ethical grounds. One important argument in favour of the practice is offered by those who believe that it is not possible to distinguish between genetic and non-genetic information, at least not for practical policy purposes such as insurance decision-making. According to the argument from indistinguishability, the use of genetic test information for insurance purposes should be permitted, because genetic test information is no different from non-genetic medical information in any relevant respect, therefore it would be inconsistent to prohibit the former whilst permitting the latter. This paper discusses and defends this argument and suggests a new, more tenable foundation.     

中小学生认知能力发展水平测验的研究

以皮亚杰的认知发展理论为基础,采用皮亚杰及其学生研究认知发展时的任务为测验题目,编制成测量中小学生认知能力发展水平的测验.通过对2240名中小学生施测,结果表明本测验不仅具有很好的信度和效度,而且也具有适中的难度.然后以一所中学特长班学生为被试,通过对他们进行测量,并将测验结果与同年级普通班学生的认知成绩进行比较,结果存在很明显的差异.最后对中小学生认知能力发展水平测量问题进行了探讨.     

Checking the Assumptions of Rasch's Model for Speed Tests

Two new tests for a model for the response times on pure speed tests by Rasch (1960) are proposed. The model is based on the assumption that the test response times are approximately gamma distributed, with known index parameters and unknown rate parameters. The rate parameters are decomposed in a subject ability parameter and a test difficulty parameter. By treating the ability as a gamma distributed random variable, maximum marginal likelihood (MML) estimators for the test difficulty parameters and the parameters of the ability distribution are easily derived. Also the model tests proposed here pertain to the framework of MML. Two tests or modification indices are proposed. The first one is focused on the assumption of local stochastic independence, the second one on the assumption of the test characteristic functions. The tests are based on Lagrange multiplier statistics, and can therefore be computed using the parameter estimates under the null model. Therefore, model violations for all items and pairs of items can be assessed as a by-product of one single estimation run. Power studies and applications to real data are included as numerical examples.     

Tucker3 hierarchical classes analysis

This paper presents a new model for binary three-way three-mode data, called Tucker3 hierarchical classes model (Tucker3-HICLAS). This new model generalizes Leenen, Van Mechelen, De Boeck, and Rosenberg's (1999) individual differences hierarchical classes model (INDCLAS). Like the INDCLAS model, the Tucker3-HICLAS model includes a hierarchical classification of the elements of each mode, and a linking structure among the three hierarchies. Unlike INDCLAS, Tucker3-HICLAS (a) does not restrict the hierarchical classifications of the three modes to have the same rank, and (b) allows for more complex linking structures among the three hierarchies. An algorithm to fit the Tucker3-HICLAS model is described and evaluated in an extensive simulation study. An application of the model to hostility data is discussed.The first author is a Research Assistant of the Fund for Scientific Research-Flanders (Belgium). The research reported in this paper was partially supported by the Research Council of K.U. Leuven (GOA/2000/02). We are grateful to Kristof Vansteelandt for providing us with an interesting data set.