Temporal concepts and predicted duration judgments

The present research investigated whether certain conceptualizations of time influence the planning fallacy or the tendency to underestimate predicted task durations. In Experiment 1, participants were presented with one of three types of primes (video, linguistic, video + linguistic) that reflected either an ego or time motion perspective (i.e. an individual moving through time vs. time moving toward an individual). Afterwards, all participants predicted the amount of time required to sort and shelve a stack of journals before actually completing the task. The results showed that across all priming conditions, subjects in the ego motion condition underestimated to a greater extent than those in the time motion condition. Experiment 2 replicated this effect and also found that underestimations are reduced when the implied duration of the experimental session is short vs. long. As a set, these findings have relevant theoretical implications and suggest some potential de-biasing techniques.     

Influence analysis for the factor analysis model with ranking data

Influence analysis is an important component of data analysis, and the local influence approach has been widely applied to many statistical models to identify influential observations and assess minor model perturbations since the pioneering work of Cook (1986) . The approach is often adopted to develop influence analysis procedures for factor analysis models with ranking data. However, as this well‐known approach is based on the observed data likelihood, which involves multidimensional integrals, directly applying it to develop influence analysis procedures for the factor analysis models with ranking data is difficult. To address this difficulty, a Monte Carlo expectation and maximization algorithm (MCEM) is used to obtain the maximum‐likelihood estimate of the model parameters, and measures for influence analysis on the basis of the conditional expectation of the complete data log likelihood at the E‐step of the MCEM algorithm are then obtained. Very little additional computation is needed to compute the influence measures, because it is possible to make use of the by‐products of the estimation procedure. Influence measures that are based on several typical perturbation schemes are discussed in detail, and the proposed method is illustrated with two real examples and an artificial example.     

Reactions to 9/11 as a function of terror management and perspective taking

The authors used terror management theory to investigate people's reactions to the terrorist attacks of 09/11/01. According to the theory, people have a primary need to eliminate or reduce existential terror in response to such horrific events as 9/11. The authors obtained people's reactions to 9/11, an event in which the threat to one's existence was more authentic than those of previous events that were imagined. The authors of the present study collected data two weeks after 9/11 from young adults on a large university campus in the U.S. Midwest. The authors asked participants about their proximal and distal reactions to 9/11 and their reasons or motives for those reactions. The results indicated that the vast majority of participants' proximal reactions to 9/11 were shock and/or disbelief, whereas their distal reactions included performing altruistic or prosocial behavior, searching for meaning or value in life, seeking or sharing information, spending time in talking to others, and making bigoted remarks about Arab Muslims. The main finding was that interpersonal communication is an important means of eliminating or reducing existential terror.     

Non‐linear structural equation models with correlated continuous and discrete data

Structural equation models (SEMs) have been widely applied to examine interrelationships among latent and observed variables in social and psychological research. Motivated by the fact that correlated discrete variables are frequently encountered in practical applications, a non‐linear SEM that accommodates covariates, and mixed continuous, ordered, and unordered categorical variables is proposed. Maximum likelihood methods for estimation and model comparison are discussed. One real‐life data set about cardiovascular disease is used to illustrate the methodologies.     

Rethinking culture and self-construal: China as a middle land

Amid criticisms of current paper-and-pencil type questionnaires measuring self-construal across cultural groups, the authors used a graphic representation scale to examine whether Anglo Canadians (N = 220) were more independent than Mainland Chinese (N = 196) and Indians (N = 212) in construing their relationships with closest family member, family members, closest friend, friends, (other) relatives, colleagues, and neighbors. Data generated 5 intriguing findings: (a) Chinese were more interdependent than Canadians but less so than Indians, indicating that Chinese culture has become more individualistic. (b) Canadians were more independent than Chinese in 6 relationship dimensions but were as interdependent as Chinese in self-closest-friend connectedness, somewhat contradicting 1 assumption of theories of independent-interdependent self-construal and individualism-collectivism (I-C). (c) Canadians were more independent than Indians in all relationship dimensions, supporting theories of independent-interdependent self-construal and I-C. (d) Chinese were as interdependent as Indians in self-closest-family-member, self-close-family-members, and self-relatives connectedness but more independent than Indians in the other categories of self-other relationships. (e) Participants' age did not have strong correlations with variables measuring self-construal in any sample, indicating that a person's attachment style may not change greatly over a lifespan. The authors discussed theoretical and methodological implications.     

Student Preferences in Divisional Studies and their Preferential Activities

Samples of preadolescents, adolescents, and young adults of middle-class backgrounds from Canadian and Asian-Indian populations were used to assess the hypothesis that with age, individuals reveal increasing differentiation in categories of personal characteristics, when evaluating themselves. The results of this cross-cultural study showed a linear increase in variance with age, in both cultural samples, and confirmed the findings of earlier investigations conducted exclusively with American-born subjects. Consistency of the findings of increasing differentiation in self-evaluations with age in the American, Canadian, and Asian samples suggests that such differentiation is a basic developmental factor in the organization of self-evaluations across cultures. In addition, it was found that, as compared with the Canadian sample, the Asian sample had significantly lower mean summation self-evaluation scores and lower mean variance scores at each age level. The implications of these cultural differences are discussed.