The Headache Symptom Questionnaire: Discriminant classificatory ability and headache syndromes suggested by a factor analysis

A brief Headache Symptom Questionnaire was administered to 129 chronic headache Sufferers. The questionnaire accurately classified 68.42% of headache subjects in their proper diagnostic category, comparable to, but statistically less accurate than, the 86.4% agreement between expert headache diagnosticians using clinical interviews. Results of a factor analysis of the Headache Symptom Questionnaire lend support for their being two commonly accepted global headache categories—vascular/migraine and muscle contraction—and one headache dimension concerned with duration of headache pain. Combined migraine-muscle contraction headache was found to be related more to migraine than to muscle contraction headache, and cluster headaches emerged as a separate clinical entity, not loading positively on any factor and loading negatively on all three.This research was supported in part by Grant NS-15235 from the National Institute of Neurological and Communicative Disorders and Stroke.     

On the base-free measure of change proposed by Tucker,Damarin and Messick

Tucker, Damarin and Messick proposed a base-free measure of change which involves the computation of residual scores that are uncorrelated with true scores on the pretest. The present note discusses this change measure and demonstrates that, because of an incorrect derivation by the authors, properties they attribute to (the coefficient for the regression of true scores from the second testing on true scores from the first testing) are, in fact, properties ofb, the ordinary regression coefficient. A correct derivation of the initial position—change correlation in terms of is obtained, and Tucker et al.'s discussion of the law of initial values is reconsidered.The preparation of this paper was supported by the Learning Research and Development Center supported in part as a research and development center by funds from the National Institute of Education.     

On rotating to smooth functions

Tucker has outlined an application of principal components analysis to a set of learning curves, for the purpose of identifying meaningful dimensions of individual differences in learning tasks. Since the principal components are defined in terms of a statistical criterion (maximum variance accounted for) rather than a substantive one, it is typically desirable to rotate the components to a more interpretable orientation. Simple structure is not a particularly appealing consideration for such a rotation; it is more reasonable to believe that any meaningful factor should form a (locally) smooth curve when the component loadings are plotted against trial number. Accordingly, this paper develops a procedure for transforming an arbitrary set of component reference curves to a new set which are mutually orthogonal and, subject to orthogonality, are as smooth as possible in a well defined (least squares) sense. Potential applications to learning data, electrophysiological responses, and growth data are indicated.Portions of this research were supported by the National Research Council of Canada, Grant A8615 to the second author. We thank Jagdeth Sheth for supplying his raw data.     

The effects of primary reward on the I.Q. performance of grade-school children as a function of initial I.Q. level

The effect of candy reward on I.Q. scores was investigated in 72 first- and second-grade children. All subjects were administered Form A of the Peabody Picture Vocabulary Test and, based upon these scores, were divided into three blocks: low, middle, and high. From each block, subjects were randomly assigned to one of three conditions (contingent reward, noncontingent reward, or no reward) that were in effect during administration of Form B. Results showed that candy given contingent upon each correct response increased I.Q. scores for the initially low scoring subjects, but had no influence on the scores of middle and high scoring subjects.     

Latent roots of random data correlation matrices with squared multiple correlations on the diagonal: A monte carlo study

In order to make the parallel analysis criterion for determining the number of factors easy to use, regression equations for predicting the logarithms of the latent roots of random correlation matrices, with squared multiple correlations on the diagonal, are presented. The correlation matrices were derived from distributions of normally distributed random numbers. The independent variables are log (N–1) and log {[n(n–1)/2]–[(i–1)n]}, whereN is the number of observations;n, the number of variables; andi, the ordinal position of the eigenvalue. The results were excellent, with multiple correlation coefficients ranging from .9948 to .9992.This research was supported by the Office of Naval Research under Contract N00014-67-A-0305-0012, Lloyd G. Humphreys, principal investigator, and by the Department of Computer Science of which Richard G. Montanelli, Jr., is a member.     

Comments on “the measurement of factorial indeterminacy”

Guttman's index of indeterminacy (2² – 1) measures the potential amount of uncertainty in picking the right alternative interpretation for a factor. When alternative solutions for a factor are equally likely to be correct, then the squared multiple correlation ² for predicting the factor from the observed variables is the average correlation _AB between independently selected alternative solutionsA andB, while var ( _AB )=(1 – ²)²/s, wheres is the dimensionality of the space in which unpredicted components of alternative solutions are to be found. When alternative solutions for the factor are not equally likely to be chosen, ² is the lower bound for E( _AB ); however, E( _AB ) need not be a modal value in the distribution of _AB . Guttman's index and E( _AB ) measure different aspects of the same indeterminacy problem.     

A look,by simulation,at the validity of some asymptotic distribution results for rotated loadings

In the last few years, a number of asymptotic results for the distribution of unrotated and rotated factor loadings have been given. This paper investigates the validity of some of these results based on simulation techniques. In particular, it looks at principal component extraction and quartimax rotation on a problem with 13 variables. The indication is that the asymptotic results are quite good.     

农村选民选举行为的结构特征

以云南省两个县八个自然村的 2 62名选民为被试 ,采用心理测量原理与技术探讨了农村选民选举行为的结构特征。结果表明 ,政见取向由“政策效应”、“民生意识”、“村民权益”和“监督机制”4个因素构成 ,非政见取向由“候选人身份”、“候选人德能”、“选民社会关系”、“候选人背景”、“选民自我利益”、“选民自我权利”和“政党意见”7个因素构成。经检验 ,由此构成的农村选举行为问卷具有较高的内部一致性 ,问卷项目具有较高的区分度。文章讨论了农村选民选举行为的结构特征及其意义。     

Caveats of non-ipsatization of basic values: A review of issues and a simulation study

Ipsatization, or a correction of variables by their common component, is routinely applied to measures of basic values. Although ipsatization has been criticized, the consequences of non-ipsatization are rarely discussed. We show that the ipsatization of values is intertwined with their definition. A common factor involved in ipsatization was suggested to represent a nuisance variable, a response style, social desirability, or other constructs. A simulation study illustrated that within-individual centering revealed more accurate value scores when the common factor was in the data, with exception of the situation when values were consistently and positively correlated with each other. We conclude that in different conditions both applying and failing to apply ipsatization can cause bias. Therefore, no general advice in regard to ipsatization can be provided.     

Agreeableness and the common core of dark traits are functionally different constructs

The Dark Factor of Personality (D) has been suggested as the basic disposition underlying dark traits, thereby representing their common core. However, it has also been argued that such commonalities reflect the low pole of Agreeableness. The present study (N = 729) employed five established inventories to model the Agreeableness construct and considered seven theoretically derived criterion variables, including one behavioral outcome. Results indicate that Agreeableness and D exhibit a substantial, but far from perfect, association of r = −.64. Further, D incrementally improved the prediction of all but one criterion measure. These results speak against the notion that the commonalities of dark traits can be reduced to low Agreeableness and rather support the contention to consider Agreeableness and D as functionally distinct constructs.