Making the illusory correlation effect appear and then disappear: The effects of increased learning

The acquisition of a negative evaluation of a fictitious minority social group in spite of the absence of any objective correlation between group membership and negative behaviours was described by Hamilton and Gifford (1976) Hamilton, D. L. and Gifford, R. K. 1976. Illusory correlation in intergroup perception: A cognitive basis of stereotypic judgments. Journal of Experimental Social Psychology, 12: 392–407. [Crossref], [Web of Science ®] , [Google Scholar] as an instance of an illusory correlation. We studied the acquisition and attenuation through time of this correlation learning effect. In two experiments we asked for participants’ judgements of two fictitious groups using an online version of a group membership belief paradigm. We tested how judgements of the two groups changed as a function of the amount of training they received. Results suggest that the perception of the illusory correlation effect is initially absent, emerges with intermediate amounts of absolute experience, but diminishes and is eliminated with increased experience. This illusory correlation effect can be considered to reflect incomplete learning rather than a bias due to information loss in judgements or distinctiveness.     

Psychometric properties of the Danish 16PF and EPQ

A Danish translation of the Cattell's 16PF has been used in studies evaluating the effects of prenatal drug exposure. This paper reports a psychometric analysis of the 16PF and Eysenck's EPQ based on a sample of 558 young Danes. Many 16PF scales had unacceptable psychometric properties (as indicated by coefficient alpha and item–total score correlations), but more satisfactory results were obtained with the EPQ N and E scales. A factor analysis of all 16PF and EPQ scales suggested a six factor solution that roughly corresponds to the second-order factor structure obtained by Krug and Johns (1986). It is concluded that the second-order factor structure should be the basis of interpretation of the 16PF in both practical and research contexts.     

On Association Coefficients for 2×2 Tables and Properties That Do Not Depend on the Marginal Distributions

We discuss properties that association coefficients may have in general, e.g., zero value under statistical independence, and we examine coefficients for 2×2 tables with respect to these properties. Furthermore, we study a family of coefficients that are linear transformations of the observed proportion of agreement given the marginal probabilities. This family includes the phi coefficient and Cohen’s kappa. The main result is that the linear transformations that set the value under independence at zero and the maximum value at unity, transform all coefficients in this family into the same underlying coefficient. This coefficient happens to be Loevinger’s H.     

Interval estimation for the intraclass correlation in dirichlet-multinomial data

When the underlying distribution is discrete with a limited number of categories, methods for interval estimation of the intraclass correlation which assume normality are theoretically inadequate for use. On the basis of large sample theory, this paper develops an asymptotic closed-form interval estimate of the intraclass correlation for the case where there is a natural score associated with each category. This paper employs Monte Carlo simulation to demonstrate that when the underlying intraclass correlation is large, the traditional interval estimator which assumes normality can be misleading. We find that when the number of classes is 20, the interval estimator proposed here can generally perform reasonably well in a variety of situations. This paper further notes that the proposed interval estimator is invariant with respect to a linear transformation. When the data are on a nominal scale, an extension of the proposed method to account for this case, as well as a discussion on the relationship between the intraclass correlation and a kappa-type measure defined here and on the limitation of the corresponding kappa-type estimator are given.The authors wish to thank the Editor, the Associate Editor, and the three referees for many valuable comments and suggestions to improve the clarity of this paper. The works for the first, the third, and the fourth authors were partially supported by grant #R01AR43025-01 from the National Institute of Arthritis and Musculoskeletal and Skin Diseases.     

Phenotypic and genotypic heterogeneity in gaucher disease: Implications for genetic counseling

Genetic counseling for Gaucher disease is complicated by the vast degree of clinical heterogeneity encountered in the disorder. Recent advances in our understanding of the molecular genetics of Gaucher disease are particularly relevant to genetic counseling. Although the identification of mutations in the glucocerebrosidase gene has enabled genotypic screening of Gaucher patients, the ability to reliably predict patient outcome on the basis of DNA studies is often limited. An appreciation of both the spectrum of clinical manifestations in Gaucher patients and the limitations of the available genotypic information is necessary when counseling patients, families and at-risk individuals.     

Fisher transformations for correlations corrected for selection and missing data

The validity of a test is often estimated in a nonrandom sample of selected individuals. To accurately estimate the relation between the predictor and the criterion we correct this correlation for range restriction. Unfortunately, this corrected correlation cannot be transformed using Fisher'sZ transformation, and asymptotic tests of hypotheses based on small or moderate samples are not accurate. We developed a Fisherr toZ transformation for the corrected correlation for each of two conditions: (a) the criterion data were missing due to selection on the predictor (the missing data were MAR); and (b) the criterion was missing at random, not due to selection (the missing data were MCAR). The twoZ transformations were evaluated in a computer simulation. The transformations were accurate, and tests of hypotheses and confidence intervals based on the transformations were superior to those that were not based on the transformations.     

Some properties of two measures of multivariate association

Two kinds of measures of multivariate association, based on Wilks' and the Bartlett-Nanda-Pillai trace criterionV, respectively, are compared in terms of properties of the univariateR ² which they generalize. A unified set of derivations of the properties is provided which are self-contained and not restricted to decompositions in canonical variates. One conclusion is that asymmetric index based on allows generalization of the multiplicative decomposition ofR ² in terms of squared partial correlations, but not the additive decomposition in terms of squared semipartial correlations, while the reverse is true for anasymmetric index based onV.We are indebted to Jos M. F. ten Berge for some fruitful discussions.     

Some effects of response-correlated increases in reinforcer magnitude on human behavior

After training under short or long fixed-interval schedules, humans responded under a modified fixed-interval schedule in which magnitude of reinforcement (X or 2X) was minimally correlated with response frequency. Response frequencies that equaled or exceeded a minimum response criterion were followed by the larger reinforcer at the end of the interval; otherwise, the smaller reinforcer was delivered. The modified schedule alternated with the baseline schedule across conditions. In a control condition, the reinforcer magnitudes produced by control subjects were yoked to those of experimental subjects. Experimental subjects, but not control subjects, showed increased responding. In addition to the baseline and modified fixed-interval schedules used in Experiment 1, subjects in Experiment 2 also responded under a second modified fixed-interval contingency in which increases in reinforcer magnitude were more highly correlated with response frequency. Experimental subjects, but not control subjects, showed increased responding under both procedures. Direct comparison of these two procedures showed that the high-correlation procedure produced greater increases in responding than did the low-correlation procedure.