Self- and other-estimates of multiple abilities in Britain and Turkey: a cross-cultural comparison of subjective ratings of intelligence

This study is part of a programmatic research effort into the determinants of self-assessed abilities. It examined cross-cultural differences in beliefs about intelligence and self- and other-estimated intelligence in two countries at extreme ends of the European continent. In all, 172 British and 272 Turkish students completed a three-part questionnaire where they estimated their parents', partners' and own multiple intelligences (Gardner (10) and Sternberg (3)). They also completed a measure of the 'big five' personality scales and rated six questions about intelligence. The British sample had more experience with IQ tests than the Turks. The majority of participants in both groups did not believe in sex differences in intelligence but did think there were race differences. They also believed that intelligence was primarily inherited. Participants rated their social and emotional intelligence highly (around one standard deviation above the norm). Results suggested that there were more cultural than sex differences in all the ratings, with various interactions mainly due to the British sample differentiating more between the sexes than the Turks. Males rated their overall, verbal, logical, spatial, creative and practical intelligence higher than females. Turks rated their musical, body-kinesthetic, interpersonal and intrapersonal intelligence as well as existential, naturalistic, emotional, creative, and practical intelligence higher than the British. There was evidence of participants rating their fathers' intelligence on most factors higher than their mothers'. Factor analysis of the ten Gardner intelligences yield two clear factors: cognitive and social intelligence. The first factor was impacted by sex but not culture; it was the other way round for the second factor. Regressions showed that five factors predicted overall estimates: sex (male), age (older), test experience (has done tests), extraversion (strong) and openness (strong). Results are discussed in terms of the growing literature in the field.     

More than,less than,or minimum,maximum: how upper and lower bounds determine subjective interval estimates

Uncertain quantities can be described by single‐point estimates of lower interval bounds (X₁), upper interval bounds (X₂), two‐bound estimates (separate estimates of X₁ and X₂), and by ranges (X₁?X₂). A price estimation task showed that single‐bound estimates phrased as “T costs more than X₁” and “T costs less than X₂,” yielded much larger intervals than “minimum X₁” and “maximum X₂.” This difference can be attributed to exclusive interpretations of X₁ and X₂ in the first case (X₁ and X₂ are unlikely values), and inclusive interpretations in the second (X₁ and X₂ are likely values). This pattern of results was replicated in other domains where participants estimated single targets. When they estimated a distribution of targets, the pattern was reversed. “Minimum” and “maximum” values of variable quantities (e.g., flight prices) were found to delimit larger intervals than “more than” and “less than” estimates. Copyright © 2006 John Wiley & Sons, Ltd.     

Judging the accuracy of a likelihood judgment: the case of smoking risk

A standard method for assessing whether people have appropriate internal representations of an event's likelihood is to check whether their subjective probability or frequency estimates for the event correspond with the assumed objective value for that event. When a person's estimate for the event exceeds its assumed objective probability or frequency, the person's expectancy for the event is concluded to be greater than warranted. This paper describes three lines of reasoning as to why conclusions of this sort can be problematic. Recently published findings as well as data from two new experiments are described to support this main thesis. The case of smoking risk is used to illustrate the more general problem, and issues that must be considered to avoid or contend with the problem are discussed. Copyright © 2002 John Wiley & Sons, Ltd.     

Bayesian estimation of a multilevel IRT model using gibbs sampling

In this article, a two-level regression model is imposed on the ability parameters in an item response theory (IRT) model. The advantage of using latent rather than observed scores as dependent variables of a multilevel model is that it offers the possibility of separating the influence of item difficulty and ability level and modeling response variation and measurement error. Another advantage is that, contrary to observed scores, latent scores are test-independent, which offers the possibility of using results from different tests in one analysis where the parameters of the IRT model and the multilevel model can be concurrently estimated. The two-parameter normal ogive model is used for the IRT measurement model. It will be shown that the parameters of the two-parameter normal ogive model and the multilevel model can be estimated in a Bayesian framework using Gibbs sampling. Examples using simulated and real data are given.     

Body image in bulimic,dieting, and normal females

The present investigation examined body-size estimation and overvaluation of a thin shape in bulimic females, females having been obese as adults who later lost weight, females with no history of obesity who were dieting, and females with no history of obesity as adults and not currently dieting. Each subject was presented with a set of seven silhouettes, one having been drawn from the subject's actual photograph and the remaining silhouettes representing 2.5, 5, and 7.5% increases and decreases in the size of certain body areas of the original figure. Subjects selected both their actual size and their ideal size. In addition, objective raters selected an ideal size for each subject. The hypotheses that bulimics would overestimate their size or overvalue an ultrathin body size as compared with other females were not supported. A history of childhood obesity appears to influence significantly body-size overestimation. Finally, the hypothesis that bulimics would appear more dissatisfied with their body image was not supported, with the three groups currently dieting appearing equally dissatisfied with their shape.The authors greatly appreciate the assistance of the graphic artist, Susan Meier.     

The Social Phobia and Social Interaction Anxiety Scales: Evaluation of Psychometric Properties

The present investigations examined the factor structure and psychometric properties of two new self-report measures of social phobia, the Social Interaction Anxiety Scale (SIAS) and the Social Phobia Scale (SPS). A confirmatory factor analysis in Study I provided support for the fit of a two-factor model of the SIAS and SPS. Internal consistency estimates were high for the original two scales with a sample of 200 undergraduates. Also, using an item parceling procedure, the obtained internal consistency reliability indices for each parcel were acceptable. Results of the CFA in Study II provided support for the factorial stability of the model identified in Study I. Furthermore, multisample analyses showed invariant patterns for factor loadings and factor correlations across 138 men and 272 women. Gender differences were not observed in the mean SIAS and SPS scale and item scores. Both scales correlated negatively and significantly with measures of social desirability. Concurrent validity was established for the scales. The SPS was less specific than the SIAS to symptoms of social phobia.     

Best linear prediction of composite universe scores

The problem of predicting universe scores for samples of examinees based on their responses to samples of items is treated. A general measurement procedure is described in which multiple test forms are developed from a table of specifications and each form is administered to a different sample of examinees. The measurement model categorizes items according to the cells of such a table, and the linear function derived for minimizing error variance in prediction uses responses to these categories. In addition, some distinctions are drawn between aspects of the approach taken here and the familiar regressed score estimates.The author thanks Robert L. Brennan, Michael J. Kolen, and Richard Sawyer for helpful comments and corrections, and anonymous reviewers for suggested improvements.     

Scale freeness in factor analysis

The notion of scale freeness does not seem to have been well understood in the factor analytic literature. It has been believed that if the loss function that is minimized to obtain estimates of the parameters in the factor model is scale invariant, then the estimates are scale free. It is shown that scale invariance of the loss function is neither a necessary nor a sufficient condition for scale freeness. A theorem that ensures scale freeness in the orthogonal factor model is given in this paper.The authors are grateful for the suggestions of the referees.     

Adults' estimates of pre-school children's verbal and motor abilities compared with those children's scores on an individual developmental test

Forty-seven mothers estimated their pre-school children's development on a psychometrically constructed multidomain mothers' inventory. Similar data were obtained for the same children from 13 pre-school teachers. The mothers' and pre-school teachers' estimates were compared to the children's scores on McCarthy Scales of Children's Abilities (MSCA). The mothers' inventory responses yielded convergent–divergent correlations with the MSCA results; in two domains out of seven, their standardized estimations were significantly lower than standardized MSCA scores, and in no case higher. Teachers' estimates deviated more than mothers' estimates from MSCA verbal and motor development scores, though in the latter case the difference between teachers and mothers were less marked. Both mothers' and teachers' difference scores (i.e. deviation of their estimates from MSCA scores) were highly correlated with the respective MSCA scores. However, when the difference scores are adjusted for shared error variance, the correlations shrink and are in most cases non-significant.