M=3.99, SD=1.67 [0=extremely left wing, 8
M=2.49, SD=0.73 [1=extremely left wing, 5=extremely right wing]2
MIsraelis=5.54, SDIsraelis=1.67, MKurds=4.80, SDKurds=1.16, MAmericans=4.19, SDAmericans=1.76, ts>2.35, ps<.020

Psychological Distance Moderates the Amplification of Shared Experience

Mage=20, SDage=1.72; 40% Caucasian/White, 34%

Grasping for Traits or Reasons? How People Grapple With Puzzling Social Behaviors

An Intention-Based Account of Perspective-Taking: Why Perspective- Taking Can Both Decrease and Increase Moral Condemnation

Ideological Differences in Anchoring and Adjustment During Social Inferences

The Malleable Efficacy of Willpower Theories

Testing the Link Between Empathy and Lay Theories of Happiness

remaining 17 items all showed primary loadings>.40
r=.14, 95% confidence interval CI=[-.05.28]

Personality Traits, Ego Development, and the Redemptive Self

washington university sentence completion test
two factorial mixed model of intraclass correlation

Beyond Affective Influences on Deontological Moral Judgment: The Role of Motivations for Prevention in the Moral Condemnation of Harm

Straying From the Righteous Path and From Ourselves: The Interplay Between Perceptions of Morality and Self-Knowledge

M=0.12, SD=0.67, p=.004; 95% confidence interval CIdifference=[.07.35]

Organizational Identity Safety Cue Transfers

Looking Forward and Looking Back: The Likelihood of an Event's Future Reoccurrence Affects Perceptions of the Time It Occurred in the Past

symmetric effect of future temporal distance estimates
psychological distance along 1 dimension can influence estimates
indirect effect of future time estimates

Do Narcissism and Emotional Intelligence Win Us Friends? Modeling Dynamics of Peer Popularity Using Inferential Network Analysis

analytic method called temporal exponential random graph model
network theory exponential random graph model
markov chain monte carlo maximum likelihood estimation
bootstrapped bias corrected 95% confidence interval

Physical Strength as a Cue to Dominance: A Data-Driven Approach