Implicit personality theory: Is it illusory?1

Several studies have found a substantial association between subjects' judgments about the co-occurrence of personality items and the items' actual co-occurrence, lending support to the validity of implicit personality theory. This work has recently been called into question by an investigation of Mirels (1976) that reported a nonsignificant relationship between judged probabilities of item pairs and the pairs' empirical coendorsement probabilities (actually calculated conditional probabilities) derived from self-report responses. Using Mirels' data as well as new data, an appreciable and highly significant association between judgments of behavioral co-occurrence and empirical coendorsement was found, when the latter was measured by correlational-type indexes instead of conditional probability. This outcome indicates that the divergent results in the Mirels investigation were due to its use of the conditional probability index as a measure of empirical coendorsement. These findings add to the accumulating body of evidence pointing to the validity of implicit personality theory.     

Fact and Fiction in Implicit Personality Theory

ABSTRACT This article reports two studies, where the accuracy of implicit personality theory (IPT) was investigated using on-line behavior counts as well as retrospective frequency estimates as standards of comparison Eight discussion groups, each comprising six members, were videotaped Their act frequencies with respect to 16 types of behavior were judged on-line using two coding schemes, each one being applied by two independent raters Five other judges estimated the act frequencies retrospectively Furthermore, judges revealed their IPT by estimating the conditional likelihood of these types of behavior It turned out that (a) retrospective judges perceive different base rates accurately, (b) the correlations among retrospectively estimated and among on-line recorded act frequencies show high correspondences, (c) IPT accurately mirrors the correlations among retrospectively estimated as well as among on-line recorded act frequencies, and (d) judges do not appropriately consider perceived base rates when estimating conditional probabilities It is concluded that IPT is considerably accurate in those respects that are important for the validity and structural fidelity of personality ratings     

Tenacious inferential illusions: Experimental fact vs. critical fancy

Tzeng and Tzeng's (1982) assertion that the results from two indices of estimated item coendorsement should not have been combined in Mirels' (1976) demonstration of inferential illusions is shown to be based on erroneous suppositions. Evidence for the equivalence of the two formats makes it clear that the separate presentation of data for each index would have yielded results and led to conclusions virtually identical to those for the combined data. The objection by Tzeng and Tzeng to Mirels' use of empirical conditional probabilities as a criterion against which to assess the veridicality of Implicit Personality Theory is also shown to be without empirical foundation. In the light of available findings, the existence of striking inaccuracies in the culturally prevalent Implicit Personality Theory seems well established.     

Implicit Personality Theory: Myth or fact? An illustration of how empirical research can miss

The present paper examines some problems in the current literature on Implicit Personality Theory (IPT) with specific reference to the controversial publications by Mirels (1976) and Jackson, Chan, and Stricker (1979). Their disputes address the question of whether individuals' estimates of trait co-occurrence accurately reflect actual (empirical) trait co-occurrence in personality ratings. The cogency of the disputes is undermined, however, by both studies' deficiences at the levels of theory, measurement, and statistical analysis. For instance, the indices used for representing estimated and empirical trait co-occurrence are neither adequately justified nor commensurate. For future personality attribution research, we discuss both the theoretical distinction between two (comparative and absolute) judgment formats frequently involved in data gathering and the empirical distinction between sophisticated and unsophisticated research strategies involved in data analysis. Finally, it was concluded that due to the residual effect of the empiricism of the 1950s and 1960s, and a lack of logical coherence between cognitive psychology, psychometric theories, and statistical data manipulations, IPT is still at an early stage of development. Future investigators should therefore develop a rigorous program with the sophistication of so-called “nomological operationalization” for a systematic investigation of IPT.     

Directional discrepancy between implicit and explicit power motives is related to well-being among managers

This study investigates explicit –implicit motive discrepancies and their effect on well-being. Participants were 382 executive managers (107 females and 275 males). Female managers had higher explicit affiliation scores than males, whereas male managers had marginally significant higher explicit power scores than females. Males and females did not differ in their implicit motives. We expected a directional discrepancy on the power motive (explicit vs. implicit: “Striving for goals without gaining pleasure from doing so”) to predict impaired well-being. Results were consistent with this hypothesis, using polynomial regression analysis with response surface methods, instead of calculating motive difference scores. Discrepancies in the achievement and affiliation motives were not related to well-being. Results are discussed considering the specificity of motive discrepancies for selected groups, such as managers, and the importance of distinguishing between absolute versus directional motive discrepancy scores in motivation research.     

Naive Probability: Model‐Based Estimates of Unique Events

We describe a dual‐process theory of how individuals estimate the probabilities of unique events, such as Hillary Clinton becoming U.S. President. It postulates that uncertainty is a guide to improbability. In its computer implementation, an intuitive system 1 simulates evidence in mental models and forms analog non‐numerical representations of the magnitude of degrees of belief. This system has minimal computational power and combines evidence using a small repertoire of primitive operations. It resolves the uncertainty of divergent evidence for single events, for conjunctions of events, and for inclusive disjunctions of events, by taking a primitive average of non‐numerical probabilities. It computes conditional probabilities in a tractable way, treating the given event as evidence that may be relevant to the probability of the dependent event. A deliberative system 2 maps the resulting representations into numerical probabilities. With access to working memory, it carries out arithmetical operations in combining numerical estimates. Experiments corroborated the theory's predictions. Participants concurred in estimates of real possibilities. They violated the complete joint probability distribution in the predicted ways, when they made estimates about conjunctions: P(A), P(B), P(A and B), disjunctions: P(A), P(B), P(A or B or both), and conditional probabilities P(A), P(B), P(B|A). They were faster to estimate the probabilities of compound propositions when they had already estimated the probabilities of each of their components. We discuss the implications of these results for theories of probabilistic reasoning.     

Unknown probabilities

From a point of view like de Finetti's, what is the judgmental reality underlying the objectivistic claim that a physical magnitude X determines the objective probability that a hypothesis H is true? When you have definite conditional judgmental probabilities for H given the various unknown values of X, a plausible answer is sufficiency, i.e., invariance of those conditional probabilities as your probability distribution over the values of X varies. A different answer, in terms of conditional exchangeability, is offered for use when such definite conditional probabilities are absent.     

A method for judging measures of stochastic dependence: further comments on the current controversy.

A large number of reports have been published on stochastic independence between implicit and explicit measures of memory. This is often taken to imply that different memory systems mediate implicit and explicit memory performance. In these cases, stochastic independence is inferred from contingency analysis of overall success rates in two memory tasks when performance in one or both of the tasks is, to a large extent, mediated by factors other than memory. Typically, the difference between performance with studied and nonstudied items is not large in implicit memory tasks. It is argued that this must be taken into account when evaluating the contingency analysis. A method is presented for estimating the relevant joint and conditional probabilities, assuming that the aspects of performance in the two tasks that are related to memory are dependent to the maximum possible extent. The method is applied to a number of published studies, and it is shown that the difference between these estimated probabilities and those given by stochastic independence is too small to allow any conclusion to be drawn about memory systems from contingency analysis of data reported in these studies.     

On the Psychological Significance of the Euclidean Representation of Implicit Personality Theory

The overall purpose of the present study was to investigate the psychological significance of the Euclidean representation of implicit personality theory (IPT) by testing the predictive usefulness of this representation. Multidimensional scaling analyses of 18 subjects' estimates of assumed trait co-occurences (IPT) gave Euclidean trait-distance matrices which were used to predict the subjects' trait-to-trait inferences. The results showed that: (1) The Euclidean representations of subjects' IPTs can be used to predict ( p < 0.10) most subjects' (14 of 18) trait-to-trait inferences; (2) The similarity between the Euclidean representation of subjects' IPTs was positively correlated (r_s = 0.43, p < 0.001) with the similarity between subjects' trait-to-trait inferences. These results suggest that the Euclidean representation of IPT has some predictive value, and thus, may at least to some extent, be justified and considered as psychologically significant.     

A goodness of fit test for the rasch model

The Rasch model is an item analysis model with logistic item characteristic curves of equal slope,i.e. with constant item discriminating powers. The proposed goodness of fit test is based on a comparison between difficulties estimated from different scoregroups and over-all estimates. Based on the within scoregroup estimates and the over-all estimates of item difficulties a conditional likelihood ratio is formed. It is shown that—2 times the logarithm of this ratio isx ²-distributed when the Rasch model is true. The power of the proposed goodness of fit test is discussed for alternative models with logistic item characteristic curves, but unequal discriminating items from a scholastic aptitude test.     

Accuracy and Bias in Stereotypes about the Social and Political Attitudes of Women and Men

In three experiments examining the accuracy of gender stereotypes about attitudes, male and female participants estimated the attitudes of men or women on items that had been administered in the General Social Survey to assess attitudes on social and political issues. Demonstrating moderate stereotypic accuracy were correlations between (a) participants' estimates of these attitudes and (b) the criterion attitudes of male and female survey respondents and sex differences in the criterion attitudes. Nevertheless, analyses of discrepancies between the estimated and criterion attitudes revealed a systematic bias by which participants consistently underestimated men's support for female-stereotypic positions on issues. Further analyses of these data suggested that this error rose from perceptions that men would oppose policies that favored women's interests. In contrast, perceived female group interest functioned as a cue to accuracy in estimating women's attitudes.     

Dyadic judgments based on conflicting samples: The failure to ignore invalid input

The present research demonstrates a so far unrecognized impediment of group performance, metacognitive myopia (Fiedler, 2012). Judges and decision-makers follow the given samples of information uncritically and neglect the metacognitive assessment of the samples' validity. Applying this notion to dyadic judgments, we instructed dyads to jointly estimate conditional probabilities p (Win|A) and p (Win|B) of Lotteries A and B. One person per dyad experienced a valid sample (winning rates conditional on lotteries). The other person experienced an invalid, reverse sample (lotteries conditional on winning). Whereas valid samples provide unbiased estimates of lotteries' winning probabilities, invalid samples can greatly misrepresent the association of winning and lotteries (depending on lottery base rates). Across three experiments, metacognitive myopia—both at the individual and at the dyadic group level—prevented participants from discriminating valid and invalid samples. Group judgments were biased toward erroneous implications of invalid samples, reflecting an equality bias among unequal group members.     

Entropy,semantic relatedness and proximity

Although word co-occurrences within a document have been demonstrated to be semantically useful, word interactions over a local range have been largely neglected by psychologists due to practical challenges. Shannon’s (Bell Systems Technical Journal, 27, 379–423, 623–665, 1948) conceptualization of information theory suggests that these interactions should be useful for understanding communication. Computational advances make an examination of local word–word interactions possible for a large text corpus. We used Brants and Franz’s (2006) dataset to generate conditional probabilities for 62,474 word pairs and entropy calculations for 9,917 words in Nelson, McEvoy, and Schreiber’s (Behavior Research Methods, Instruments, & Computers, 36, 402–407, 2004) free association norms. Semantic associativity correlated moderately with the probabilities and was stronger when the two words were not adjacent. The number of semantic associates for a word and the entropy of a word were also correlated. Finally, language entropy decreases from 11 bits for single words to 6 bits per word for four-word sequences. The probabilities and entropies discussed here are included in the supplemental materials for the article.     

How to administer the Initial Preference Task

Individuals like their name letters more than non‐name letters. This effect has been termed the Name Letter Effect (NLE) and is widely exploited to measure implicit (i.e. automatic, unconscious) self‐esteem, predominantly by means of the Initial Preference Task (IPT). Methodological research on how to best administer the IPT is, however, scarce. In order to bridge this gap, the present paper assessed the advantages and disadvantages of different types of IPT administrations with two meta‐analyses (k = 49; N = 11,514) and a follow‐up experiment (N = 449). As a result, a new type of administration is recommended which (1) treats the effects of the first and the last name initials separately, (2) uses a duplicate administration for reliability reasons, (3) uses the likability as well as the attractiveness item wording and (4) exploits not only letters but also numbers (i.e. birthday number effect) to measure implicit self‐esteem. Copyright © 2011 John Wiley & Sons, Ltd.     

Confidence depends on level of aggregation

The credible intervals that people set around their point estimates are typically too narrow (cf. Lichtenstein, Fischhoff, & Phillips, 1982). That is, a set of many such intervals does not contain the actual values of the criterion variables as often as it should given the probability assigned to this event for each estimate. The typical interpretation of such data is that people are overconfident about the accuracy of their judgments. This paper presents data from two studies showing the typical levels of overconfidence for individual estimates of unknown quantities. However, data from the same subjects on a different measure of confidence for the same items, their own global assessment for the set of multiple estimates as a whole, showed significantly lower levels of confidence and overconfidence than their average individual assessment for items in the set. It is argued that the event and global assessments of judgment quality are fundamentally different and are affected by unique psychological processes. Finally, we discuss the implications of a difference between confidence in single and multiple estimates for confidence research and theory.     

Using the conditional grade-of-membership model to assess judgment accuracy

Consider the case whereJ instruments are used to classify each ofI objects relative toK nominal categories. The conditional grade-of-membership (GoM) model provides a method of estimating the classification probabilities of each instrument (or judge) when the objects being classified consist of both pure types that lie exclusively in one ofK nominal categories, and mixtures that lie in more than one category. Classification probabilities are identifiable whenever the sample of GoM vectors includes pure types from each category. When additional, relatively mild, assumptions are made about judgment accuracy, the identifiable correct classification probabilities are the greatest lower bounds among all solutions that might correspond to the observed multinomial process, even when the unobserved GoM vectors do not include pure types from each category. Estimation using the conditional GoM model is illustrated on a simulated data set. Further simulations show that the estimates of the classification probabilities are relatively accurate, even when the sample contains only a small percentage of approximately pure objects.The authors thank Max A. Woodbury, Kenneth G. Manton and H. Dennis Tolley for their help and four anonymous Psychometrika reviewers (including an associate editor) for their beneficial expository and technical suggestions. This work was supported by the Dean's Fund for Summer Research, Owen Graduate School of Management, Vanderbilt University.     

An Investigation of Differential Relationships of Implicit and Explicit Aggression: Validation of an Arabic Version of the Conditional Reasoning Test for Aggression

Abstract

Most personality research in the workplace relies on self-reports. Although self-report measures are believed to assess the explicit aspect of personality, a more recent approach for assessing implicit personality is based on conditional reasoning. The Conditional Reasoning Test for Aggression (CRT–A) was developed to assess implicit cognitions that justify aggressive behavior. The integrative model of personality proposes that both the explicit and implicit personality interact together to predict different behavioral outcomes. The results of this investigation are reported in two studies. The purpose of Study 1 was to adapt the CRT–A to the Arabic language and to examine its validity evidence using a large sample of Egyptian employees (n?=?1,046). Study 2 aimed at examining the differential relationships of implicit and explicit components of aggressive personality in explaining different forms of aggressive behavior variance (n?=?271). The results of Study 1 revealed that the psychometric properties of the adapted Arabic version of CRT–A were similar to those obtained for the United States. In addition, factor analysis results were consistent with the psychological theory used to build the conditional reasoning problems. The results of Study 2 provide substantial empirical support for the integrative model of assessment of aggression.     

The assessment of knowledge and learning in competence spaces: The gain–loss model for dependent skills

The gain–loss model (GaLoM) is a formal model for assessing knowledge and learning. In its original formulation, the GaLoM assumes independence among the skills. Such an assumption is not reasonable in several domains, in which some preliminary knowledge is the foundation for other knowledge. This paper presents an extension of the GaLoM to the case in which the skills are not independent, and the dependence relation among them is described by a well‐graded competence space. The probability of mastering skill s at the pretest is conditional on the presence of all skills on which s depends. The probabilities of gaining or losing skill s when moving from pretest to posttest are conditional on the mastery of s at the pretest, and on the presence at the posttest of all skills on which s depends. Two formulations of the model are presented, in which the learning path is allowed to change from pretest to posttest or not. A simulation study shows that models based on the true competence space obtain a better fit than models based on false competence spaces, and are also characterized by a higher assessment accuracy. An empirical application shows that models based on pedagogically sound assumptions about the dependencies among the skills obtain a better fit than models assuming independence among the skills.     

How probability theory explains the conjunction fallacy

The conjunction fallacy occurs when people judge a conjunctive statement B‐and‐A to be more probable than a constituent B, in contrast to the law of probability that P(B ∧ A) cannot exceed P(B) or P(A). Researchers see this fallacy as demonstrating that people do not follow probability theory when judging conjunctive probability. This paper shows that the conjunction fallacy can be explained by the standard probability theory equation for conjunction if we assume random variation in the constituent probabilities used in that equation. The mathematical structure of this equation is such that random variation will be most likely to produce the fallacy when one constituent has high probability and the other low, when there is positive conditional support between the constituents, when there are two rather than three constituents, and when people rank probabilities rather than give numerical estimates. The conjunction fallacy has been found to occur most frequently in exactly these situations. Copyright © 2008 John Wiley & Sons, Ltd.