Emotional disturbances and their interaction with neuropsychological deficits

The interaction and relationships between neuropsychological tests (which are principally oriented to intellectual and cognitive abilities) and tests of personality and emotional status are complex, but nevertheless important in the clinical assessment of brain-damaged persons. Are indications of emotional disturbances to be expected as a direct consequence of brain damage? If so, how can the indications of emotional disturbances be differentiated from results obtained with psychiatrically disturbed (non-brain-damaged) subjects? Some authors have presumed that emotional disturbances, such as depression, acute anxiety, etc., in their own right cause impaired performances on neuropsychological tests, whereas other authors have proposed that brain damage predisposes the individual to demonstrate evidence of emotional disturbances. If emotional disturbances cause impairment on neuropsychological tests, why is it that so many emotionally disturbed persons without brain damage tend to perform normally on neuropsychological tests? This review of relevant publications considers (1) different general approaches to these questions and their implications for neuropsychology, (2) evidence of differential sensitivity to brain damage of neuropsychological and emotional instruments, (3) the sensitivity and specificity of self-assessments and complaints of head-injured subjects, (4) MMPI findings among head-injured subjects and in interaction with neuropsychological measurements, and (5) principles and guidelines that may be of value in clinical application of findings reported in the literature.     

Comparing several robust tests of stochastic equality with ordinally scaled variables and small to moderate sized samples

In a comparison of 2 treatments, if outcome scores are denoted by X in 1 condition and by Y in the other, stochastic equality is defined as P(X < Y) = P(X > Y). Tests of stochastic equality can be affected by characteristics of the distributions being compared, such as heterogeneity of variance. Thus, various robust tests of stochastic equality have been proposed and are evaluated here using a Monte Carlo study with sample sizes ranging from 10 to 30. Three robust tests are identified that perform well in Type I error rates and power except when extremely skewed data co-occur with very small n. When tests of stochastic equality might be preferred to tests of means is also considered.     

Point-biserial correlation: Interval estimation,hypothesis testing,meta-analysis,and sample size determination

The point-biserial correlation is a commonly used measure of effect size in two-group designs. New estimators of point-biserial correlation are derived from different forms of a standardized mean difference. Point-biserial correlations are defined for designs with either fixed or random group sample sizes and can accommodate unequal variances. Confidence intervals and standard errors for the point-biserial correlation estimators are derived from the sampling distributions for pooled-variance and separate-variance versions of a standardized mean difference. The proposed point-biserial confidence intervals can be used to conduct directional two-sided tests, equivalence tests, directional non-equivalence tests, and non-inferiority tests. A confidence interval for an average point-biserial correlation in meta-analysis applications performs substantially better than the currently used methods. Sample size formulas for estimating a point-biserial correlation with desired precision and testing a point-biserial correlation with desired power are proposed. R functions are provided that can be used to compute the proposed confidence intervals and sample size formulas.     

Changes over time in the black–white difference on mental tests: Evidence from the children of the 1979 cohort of the National Longitudinal Survey of Youth

Data for three Peabody achievement tests and for the Peabody picture vocabulary test administered to children of women in the 1979 cohort of the National Longitudinal Survey of Youth show that the black–white difference did not diminish for this sample of children born from the mid 1970s through the mid 1990s. This finding persists after entering covariates for the child's age and family background variables. It is robust across alternative samples and specifications of the model. The analysis supplements other evidence that shows no narrowing of the black–white difference in academic achievement tests since the late 1980s and is inconsistent with recent evidence that narrowing occurred in IQ standardizations during the same period. A hypothesis for reconciling this inconsistency is proposed.     

Comparing score tests and other local dependence diagnostics for the graded response model

Score tests for identifying locally dependent item pairs have been proposed for binary item response models. In this article, both the bifactor and the threshold shift score tests are generalized to the graded response model. For the bifactor test, the generalization is straightforward; it adds one secondary dimension associated only with one pair of items. For the threshold shift test, however, multiple generalizations are possible: in particular, conditional, uniform, and linear shift tests are discussed in this article. Simulation studies show that all of the score tests have accurate Type I error rates given large enough samples, although their small‐sample behaviour is not as good as that of Pearson's Χ² and M₂ as proposed in other studies for the purpose of local dependence (LD) detection. All score tests have the highest power to detect the LD which is consistent with their parametric form, and in this case they are uniformly more powerful than Χ² and M₂; even wrongly specified score tests are more powerful than Χ² and M₂ in most conditions. An example using empirical data is provided for illustration.     

Approaches to univocal factor scores

Two current methods of deriving common-factor scores from tests are briefly examined and rejected. One of these estimates a score from a multiple-regression equation with as many terms as there are tests in the battery. The other limits the equation to a few tests heavily saturated with the desired factor, with or without tests used to suppress the undesired factors. In the proposed methods, the single best test for each common factor is the starting point. Such a test ordinarily has a very few undesired factors to be suppressed, frequently only one. The suppression test should be univocal, or nearly so. Fortunately, there are relatively univocal tests for factors that commonly require suppression. Equations are offered by which the desired-factor test and a single suppression test can be weighted in order to achieve one or more objectives. Among the objectives are (1) maximizing the desired factor variance, (2) minimizing the undesired factor variance, (3) a compromise, in which the undesired variance is materially reduced without loss in desired variance, and (4) a change to any selected ratio of desired to undesired variance. A more generalized solution is also suggested. The methods can be extended in part to the suppression of more than one factor. Equations are derived for the suppression of two factors.     

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.     

Tests of Homoscedasticity,Normality, and Missing Completely at Random for Incomplete Multivariate Data

Test of homogeneity of covariances (or homoscedasticity) among several groups has many applications in statistical analysis. In the context of incomplete data analysis, tests of homoscedasticity among groups of cases with identical missing data patterns have been proposed to test whether data are missing completely at random (MCAR). These tests of MCAR require large sample sizes n and/or large group sample sizes n _i , and they usually fail when applied to nonnormal data. Hawkins (Technometrics 23:105–110, 1981) proposed a test of multivariate normality and homoscedasticity that is an exact test for complete data when n _i are small. This paper proposes a modification of this test for complete data to improve its performance, and extends its application to test of homoscedasticity and MCAR when data are multivariate normal and incomplete. Moreover, it is shown that the statistic used in the Hawkins test in conjunction with a nonparametric k-sample test can be used to obtain a nonparametric test of homoscedasticity that works well for both normal and nonnormal data. It is explained how a combination of the proposed normal-theory Hawkins test and the nonparametric test can be employed to test for homoscedasticity, MCAR, and multivariate normality. Simulation studies show that the newly proposed tests generally outperform their existing competitors in terms of Type I error rejection rates. Also, a power study of the proposed tests indicates good power. The proposed methods use appropriate missing data imputations to impute missing data. Methods of multiple imputation are described and one of the methods is employed to confirm the result of our single imputation methods. Examples are provided where multiple imputation enables one to identify a group or groups whose covariance matrices differ from the majority of other groups.     

Exact person fit indexes for the rasch model for arbitrary alternatives

A new algorithm for obtaining exact person fit indexes for the Rasch model is introduced which realizes most powerful tests for a very general family of alternative hypotheses, including tests concerning DIF as well as model-deviating item correlations. The method is also used as a goodness-of-fit test for whole data sets where the item parameters are assumed to be known. For tests with 30 items at most, exact values are obtained, for longer tests a Monte Carlo-algorithm is proposed. Simulated examples and an empirical investigation demonstrate test power and applicability to item elimination.The author wishes to thank Elisabeth Ponocny-Seliger and the reviewers for many helpful comments. All exact goodness-of-fit tests proposed in this article are implemented in the menu-driven program T-Rasch 1.0 by Ponocny and Ponocny-Seliger (1999) which can be obtained from ProGAMMA (WWW: http://www.gamma.rug.nl) and also performs nonparametric tests.     

Correlation and prediction in ordinal test theory

Based on the test theory model for ordinal measurements proposed by Schulman and Haden, the present paper considers correlations between tests, attenuation, regressions involving true and observed scores, and prediction of test reliability.The population correlation between tests is shown to be related to the expected sample correlation for samples of sizen ₁ andn ₂. Errors of estimation, measurement and prediction are found to be similar to their counterparts in interval test theory, while attenuation is identical to its counterpart. The bias in estimating population reliability from sample data is compared for Kendall's tau and Spearman's rho.The author wishes to thank the referees for their helpful comments on an earlier draft of this paper, and in particular, for the suggested alternative methods of establishing some of the presented results.     

Time-limit tests: estimating their reliability and degree of speeding

Non-spurious methods are needed for estimating the coefficient of equivalence for speeded tests from single-trial data. Spuriousness in a split-half estimate depends on three conditions; the split-half method may be used if any of these is demonstrated to be absent. A lower-bounds formula,r _c, is developed. An empirical trial of this coefficient and other bounds proposed by Gulliksen demonstrates that, for moderately speeded tests, the coefficient of equivalence can be determined approximately from single-trial data. It is proposed that the degree to which tests are speeded be investigated explicitly, and an index is advanced to define this concept.     

Extending Psychometric Norms for Pre-Cardiac Transplantation Evaluations: The Florida Cohort, 1990–1996

Multidisciplinary pre-cardiac transplantation evaluations determine an individual's ability to benefit from potential transplantation. Psychologists are routinely consulted to perform psychological evaluations and testing to examine the candidate's current functioning and to forecast future functioning in the event of transplantation. The establishment of appropriate norms for psychological tests is an ethical imperative to provide high quality psychological consultations that maximize the utility of information gathered. The purpose of this paper is to present pre-cardiac transplant norms for a battery of psychological tests in a large population of consecutive transplant candidates. Together with other recently published norms on alternative test batteries, these norms allow the transplant psychologist to select from a range of psychological tests that span multiple domains of critical importance including the affective, behavioral, coping, cognitive, and health related quality of life domains. These norms appear to set a standard of practice for the use of psychological tests by a consulting transplantation psychologist.     

Evaluating socioeconomic status bias in the WISC-R

The use of intelligence tests in making special education placement decisions for children has come under repeated scrutiny in recent years. Arguments for and against the use of IQs have centered around the issue of test bias. In California a permanent moratorium on the use of intelligence tests in placing minority group children into classes for the educable retarded has been handed down by the court. One defense proposed by advocates of mental testing has been that the tests are biased against socially and economically disadvantaged groups irrespective of race. According to Clarizio (1978), if a test predicts equally well for two groups it can not legitimately be described as biased. The purpose of this investigation was to evaluate the test bias of the Verbal IQ as measured by the Wechsler Intelligence Scale for Children-Revised in relation to predictions of academic achievement in two different socioeconomic status groups. The results indicated that Verbal IQs are not biased with respect to socioeconomic status. Derived regression equations are presented along with an analysis to inspect the statistical power of the original tests.     

Heterosis doesn't cause the Flynn effect: a critical examination of Mingroni (2007)

Mingroni (2007) proposed that heterosis or hybrid vigor may be the principal driver of the Flynn effect--the tendency for IQ scores to increase at a rate of approximately 3 points per decade. This model was presented as a resolution to the IQ paradox--the observation that IQ scores have been increasing despite their high adult heritability--on the basis that substantial changes in IQ can only be accounted for by changes in underlying genetic factors. It is here argued that this model is predicated upon a misconception of the Flynn effect, which is most pronounced on the least g-loaded components of cognitive ability tests and is uncorrelated with genetic effects such as inbreeding depression scores (which are correlated with the g loadings of tests). Evidence supportive of the recently proposed life history model of the Flynn effect is presented. In the discussion, other theoretical objections to the heterosis model are also considered. On this basis, it is concluded that the Flynn effect is strongly entwined with developmental status and that heterosis cannot be its principal cause.     

Lesions of the basal ganglia, thalamus, and deep white matter: Differential effects on language functions

Forty-five patients with unilateral demarcated vascular lesions in the basal ganglia, the thalamus and the deep white matter were investigated with an "aphasia battery." Patients with basal ganglia lesions performed worse than both other groups in tests of articulation, syntax, and lexical functions. The deficit of patients with basal ganglia lesions on all expressive language modalities was lateralized to the left hemisphere. Patients with left thalamic lesions showed impairments of speech fluency and in the Token Test. Patients with white matter lesions alone showed no effect of laterality in tests of language functions. The results are discussed on the basis of a recent theory of the participation of the deep nuclei in language processing.     

罗夏测验在西方近10年的最新发展

近10年来, 罗夏综合系统不断发展, 新增了XA%与WDA%、知觉&#8722;思维指数PTI、GHR:PHR等多个指标, 修改了8个群变量, 删除了精神分裂SCZI指标。这些新调整虽然不是本质性的, 但使得罗夏综合系统内容更加完善, 信度和效度不断提高, 更加精确化和标准化, 成为西方不可或缺的心理测验工具。尽管罗夏综合系统不断发展, 但仍然存在着操作过于复杂、功能还需要进一步完善等问题。罗夏综合系统作为一个代表性的投射测验, 与其它客观测验组成了一个完整的心理测量体系, 会发挥越来越大的作用。     

A method of score conversion through item statistics

A method is presented for converting the scores on one form of a test to those on another form of the same test. The method is particularly applicable to the case where each form has been administered to a different group and the only link between the two forms is a subset of items common to both. The proposed method, called theitem method of conversion, has been applied to several tests for which other methods of conversion are available for comparison. The necessary data are limited to tests for which the total score is the criterion for item analyses. The method gives highly satisfactory results for all the tests to which it has been applied, particularly when the two groups are rather different, in which case the delta method (a different item method) is inappropriate.The authors are only two of a group, including W. H. Angoff, F. M. Lord, and M. K. Schultz, all of whom have made important contributions to this paper.     

A simple and powerful test for autocorrelated errors in OLS intervention models

The important assumption of independent errors should be evaluated routinely in the application of interrupted time-series regression models. The two most frequently recommended tests of this assumption [Mood's runs test and the Durbin-Watson (D-W) bounds test] have several weaknesses. The former has poor small sample Type I error performance and the latter has the bothersome property that results are often declared to be "inconclusive." The test proposed in this article is simple to compute (special software is not required), there is no inconclusive region, an exact p-value is provided, and it has good Type I error and power properties relative to competing procedures. It is shown that these desirable properties hold when design matrices of a specified form are used to model the response variable. A Monte Carlo evaluation of the method, including comparisons with other tests (viz., runs, D-W bounds, and D-W beta), and examples of application are provided.     

Statistical modelling of network panel data: goodness of fit

Networks of relationships between individuals influence individual and collective outcomes and are therefore of interest in social psychology, sociology, the health sciences, and other fields. We consider network panel data, a common form of longitudinal network data. In the framework of estimating functions, which includes the method of moments as well as the method of maximum likelihood, we propose score-type tests. The score-type tests share with other score-type tests, including the classic goodness-of-fit test of Pearson, the property that the score-type tests are based on comparing the observed value of a function of the data to values predicted by a model. The score-type tests are most useful in forward model selection and as tests of homogeneity assumptions, and possess substantial computational advantages. We derive one-step estimators which are useful as starting values of parameters in forward model selection and therefore complement the usefulness of the score-type tests. The finite-sample behaviour of the score-type tests is studied by Monte Carlo simulation and compared to t-type tests.     

项目间多维测验作答时间数据分析：潜在特质速度间效应建模

随着计算机测验使用的普及化,被试在心理与教育测验上的作答反应时的获取也越发便利。为了充分利用项目反应时信息,单维与多维的反应时模型相继被提出。然后,在项目间多维反应时数据中,潜在特质速度之间可能存在共同关系（比如,层阶关系）,此时现有的反应时模型并不能适用。基于此,本研究提出了高阶对数正态反应时模型与双因子对数正态反应时模型。在模拟研究中,高阶对数正态反应时模型与双因子对数正态反应时模型的各参数都能被准确估计。在瑞文标准推理测验的三组测验项目的反应时数据中,双因子对数正态反应时模型表现出更为优秀的拟合效果,同时基于多个统计量说明了局部与全局潜在特质速度同时存在的必要性。因此,在项目间多维测验反应时数据分析中,非常有必要考虑多维潜在特质速度之间的共同效应。