Draining the pond: why Singer’s defense of the duty to aid the world’s poor is self-defeating

Philosophical Studies - Peter Singer’s defense of the duty to aid the world’s poor by the pond analogy is self-defeating. It cannot be both true that you ought to save the drowning...     

Counterfactual closeness and predicted affect

Empirical research on counterfactual thinking has found a closeness effect: people report higher negative affect if an actual outcome is close to a better counterfactual outcome. However, it remains unclear what actually is a “close” miss. In three experiments that manipulate close counterfactuals, closeness effects were found only when closeness was unambiguously defined either with respect to a contrasted alternative, or with respect to a categorical boundary. In a real task people failed to report greater negative affect when encountering a close numerical miss, while they predicted greater negative affect hypothetically. These results show that counterfactual closeness effects on affect depend on closeness being accessible and unambiguously defined.     

Parameter recovery and model selection in mixed Rasch models

This study examines the precision of conditional maximum likelihood estimates and the quality of model selection methods based on information criteria (AIC and BIC) in mixed Rasch models. The design of the Monte Carlo simulation study included four test lengths (10, 15, 25, 40), three sample sizes (500, 1000, 2500), two simulated mixture conditions (one and two groups), and population homogeneity (equally sized subgroups) or heterogeneity (one subgroup three times larger than the other). The results show that both increasing sample size and increasing number of items lead to higher accuracy; medium-range parameters were estimated more precisely than extreme ones; and the accuracy was higher in homogeneous populations. The minimum-BIC method leads to almost perfect results and is more reliable than AIC-based model selection. The results are compared to findings by Li, Cohen, Kim, and Cho (2009) and practical guidelines are provided.