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251.
Agents of Prosociality: Agency Affirmation Promotes Mutual Prosocial Tendencies and Behavior Among Conflicting Groups
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Ilanit SimanTov‐Nachlieli Nurit Shnabel Anna Lisa Aydin Johannes Ullrich 《Political psychology》2018,39(2):445-463
Members of conflicting groups are motivated to restore their ingroup's agency, leading to antisocial tendencies against the outgroup. The present research tested the hypothesis that affirming conflicting groups' agency would increase their members' mutual prosociality. The effectiveness of agency affirmation was demonstrated in three contexts of conflict between groups: Switzerland and the EU following the 2014 referendum (Study 1), Israelis and Palestinians (Study 2), and Israeli rightists and leftists (Study 3). Study 1 found that in a nonconflictual context Swiss participants prioritized their moral (prosocial) over agentic goals, yet in the context of conflict with the EU, they prioritized their agentic over moral goals. This “primacy‐of‐agency” effect, however, was eliminated once their ingroup's agency was affirmed. Studies 2 and 3 demonstrated the positive effect of agency affirmation on prosociality among Israelis referring to Palestinians and Israeli rightists and leftists referring to the adversarial political camp. This effect was mediated by group members' readiness to relinquish some power for the sake of morality. Pointing to the importance of the affirmation's specific content, Studies 2 and 3 demonstrated that morality affirmation failed to increase prosociality. As such, the present research puts forward a promising strategy to reduce hostility and promote prosociality between conflicting groups. 相似文献
252.
Peida Zhan Hong Jiao Dandan Liao 《The British journal of mathematical and statistical psychology》2018,71(2):262-286
To provide more refined diagnostic feedback with collateral information in item response times (RTs), this study proposed joint modelling of attributes and response speed using item responses and RTs simultaneously for cognitive diagnosis. For illustration, an extended deterministic input, noisy ‘and’ gate (DINA) model was proposed for joint modelling of responses and RTs. Model parameter estimation was explored using the Bayesian Markov chain Monte Carlo (MCMC) method. The PISA 2012 computer-based mathematics data were analysed first. These real data estimates were treated as true values in a subsequent simulation study. A follow-up simulation study with ideal testing conditions was conducted as well to further evaluate model parameter recovery. The results indicated that model parameters could be well recovered using the MCMC approach. Further, incorporating RTs into the DINA model would improve attribute and profile correct classification rates and result in more accurate and precise estimation of the model parameters. 相似文献
253.
Shiyu Wang 《The British journal of mathematical and statistical psychology》2018,71(2):300-333
The maximum likelihood classification rule is a standard method to classify examinee attribute profiles in cognitive diagnosis models (CDMs). Its asymptotic behaviour is well understood when the model is assumed to be correct, but has not been explored in the case of misspecified latent class models. This paper investigates the asymptotic behaviour of a two-stage maximum likelihood classifier under a misspecified CDM. The analysis is conducted in a general restricted latent class model framework addressing all types of CDMs. Sufficient conditions are proposed under which a consistent classification can be obtained by using a misspecified model. Discussions are also provided on the inconsistency of classification under certain model misspecification scenarios. Simulation studies and a real data application are conducted to illustrate these results. Our findings can provide some guidelines as to when a misspecified simple model or a general model can be used to provide a good classification result. 相似文献
254.
Drawing from the intimacy process model and data from 5,042 individuals who remained partnered across Waves 1 and 2 of the German Panel Analysis of Intimate Relationships and Family Dynamics (pairfam), this study examined the contributions of traditional gender role attitudes and relationship efficacy in predicting levels of self-disclosure within an intimate relationship. Independent samples t-tests demonstrated females scored higher than males on self-disclosure and relationship efficacy measures but lower on traditional gender role attitudes. An ordinary least squares regression analysis revealed relationship efficacy was a stronger predictor of self-disclosure compared to traditional gender role attitudes, which were not associated with self-disclosure. The findings suggest attitudes with an interpersonal motivational system may be especially important for setting the intimacy process into motion within an intimate union. 相似文献
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257.
Bryan Klapes Steven Riley J. J McDowell 《Journal of the experimental analysis of behavior》2018,109(2):336-348
A direct‐suppression, or subtractive, model of punishment has been supported as the qualitatively and quantitatively superior matching law‐based punishment model (Critchfield, Paletz, MacAleese, & Newland, 2003; de Villiers, 1980; Farley, 1980). However, this conclusion was made without testing the model against its predecessors, including the original (Herrnstein, 1961) and generalized (Baum, 1974) matching laws, which have different numbers of parameters. To rectify this issue, we reanalyzed a set of data collected by Critchfield et al. (2003) using information theoretic model selection criteria. We found that the most advanced version of the direct‐suppression model (Critchfield et al., 2003) does not convincingly outperform the generalized matching law, an account that does not include punishment rates in its prediction of behavior allocation. We hypothesize that this failure to outperform the generalized matching law is due to significant theoretical shortcomings in model development. To address these shortcomings, we present a list of requirements that all punishment models should satisfy. The requirements include formal statements of flexibility, efficiency, and adherence to theory. We compare all past punishment models to the items on this list through algebraic arguments and model selection criteria. None of the models presented in the literature thus far meets all of the requirements. 相似文献
258.
Chuanji Gao Douglas H. Wedell Jongwan Kim Christine E. Weber 《Cognition & emotion》2018,32(3):516-529
Two experiments examined how affective values from visual and auditory modalities are integrated. Experiment 1 paired music and videos drawn from three levels of valence while holding arousal constant. Experiment 2 included a parallel combination of three levels of arousal while holding valence constant. In each experiment, participants rated their affective states after unimodal and multimodal presentations. Experiment 1 revealed a congruency effect in which stimulus combinations of the same extreme valence resulted in more extreme state ratings than component stimuli presented in isolation. An interaction between music and video valence reflected the greater influence of negative affect. Video valence was found to have a significantly greater effect on combined ratings than music valence. The pattern of data was explained by a five parameter differential weight averaging model that attributed greater weight to the visual modality and increased weight with decreasing values of valence. Experiment 2 revealed a congruency effect only for high arousal combinations and no interaction effects. This pattern was explained by a three parameter constant weight averaging model with greater weight for the auditory modality and a very low arousal value for the initial state. These results demonstrate key differences in audiovisual integration between valence and arousal. 相似文献
259.
Automated verbal credibility assessment of intentions: The model statement technique and predictive modeling
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Bennett Kleinberg Yaloe van der Toolen Aldert Vrij Arnoud Arntz Bruno Verschuere 《Applied cognitive psychology》2018,32(3):354-366
Recently, verbal credibility assessment has been extended to the detection of deceptive intentions, the use of a model statement, and predictive modeling. The current investigation combines these 3 elements to detect deceptive intentions on a large scale. Participants read a model statement and wrote a truthful or deceptive statement about their planned weekend activities (Experiment 1). With the use of linguistic features for machine learning, more than 80% of the participants were classified correctly. Exploratory analyses suggested that liars included more person and location references than truth‐tellers. Experiment 2 examined whether these findings replicated on independent‐sample data. The classification accuracies remained well above chance level but dropped to 63%. Experiment 2 corroborated the finding that liars' statements are richer in location and person references than truth‐tellers' statements. Together, these findings suggest that liars may over‐prepare their statements. Predictive modeling shows promise as an automated veracity assessment approach but needs validation on independent data. 相似文献
260.
Laura F. Bringmann Emilio Ferrer Ellen L. Hamaker Denny Borsboom Francis Tuerlinckx 《Multivariate behavioral research》2018,53(3):293-314
Emotion dynamics are likely to arise in an interpersonal context. Standard methods to study emotions in interpersonal interaction are limited because stationarity is assumed. This means that the dynamics, for example, time-lagged relations, are invariant across time periods. However, this is generally an unrealistic assumption. Whether caused by an external (e.g., divorce) or an internal (e.g., rumination) event, emotion dynamics are prone to change. The semi-parametric time-varying vector-autoregressive (TV-VAR) model is based on well-studied generalized additive models, implemented in the software R. The TV-VAR can explicitly model changes in temporal dependency without pre-existing knowledge about the nature of change. A simulation study is presented, showing that the TV-VAR model is superior to the standard time-invariant VAR model when the dynamics change over time. The TV-VAR model is applied to empirical data on daily feelings of positive affect (PA) from a single couple. Our analyses indicate reliable changes in the male’s emotion dynamics over time, but not in the female’s—which were not predicted by her own affect or that of her partner. This application illustrates the usefulness of using a TV-VAR model to detect changes in the dynamics in a system. 相似文献