Off-line authorship effects in action perception

Does the perception of our actions differ from the perception of other individuals' actions when we observe them, like other individual's actions, in an offline perspective? Previous studies, using recognition as well as prediction judgments, suggest that it does even if the stimulus information is reduced to a single moving point-light. Here, we assessed whether this difference also affects the timing of actions. This was tested in two experiments, using a specific synchronization task. After some practice, self-generated action events were anticipated faster than other action events, provided that the anticipation could not be accomplished sufficiently well on the basis of easily detectable cues. The results are discussed with regard to the previous findings of off-line authorship effects in action perception.     

Direction dependence analysis: A framework to test the direction of effects in linear models with an implementation in SPSS

In nonexperimental data, at least three possible explanations exist for the association of two variables x and y: (1) x is the cause of y, (2) y is the cause of x, or (3) an unmeasured confounder is present. Statistical tests that identify which of the three explanatory models fits best would be a useful adjunct to the use of theory alone. The present article introduces one such statistical method, direction dependence analysis (DDA), which assesses the relative plausibility of the three explanatory models on the basis of higher-moment information about the variables (i.e., skewness and kurtosis). DDA involves the evaluation of three properties of the data: (1) the observed distributions of the variables, (2) the residual distributions of the competing models, and (3) the independence properties of the predictors and residuals of the competing models. When the observed variables are nonnormally distributed, we show that DDA components can be used to uniquely identify each explanatory model. Statistical inference methods for model selection are presented, and macros to implement DDA in SPSS are provided. An empirical example is given to illustrate the approach. Conceptual and empirical considerations are discussed for best-practice applications in psychological data, and sample size recommendations based on previous simulation studies are provided.     

Determinants of memory development in childhood and adolescence

Research on the development of memory has a long history and constitutes one of the most active research areas in the field of cognitive development. In this article, we first describe major historical developments in the literature on children's memory, focusing on systematic research that began in the late 1960s. We then examine new developments in the field, describing four important lines of inquiry: (a) the development of implicit memory, (b) short‐ and long‐term memory development in infancy, (c) longitudinal research on memory strategies and metamemory, and (d) developmental cognitive neuroscience of memory. Finally, promising lines of future research on memory development are briefly discussed.     

Like mother,like child? Maternal determinants of children's early social-emotional development

Social-Emotional competencies evolve early in life. For example, early emotion regulation is learned primarily in the context of mother–child interaction, which may allow for maternal influences to shape children's social-emotional development. The aim of the current study was to longitudinally examine maternal determinants of children's early social-emotional development in a community-based sample of first-time mothers (N = 61, aged 22–39 years). Specifically, we used structural equation modeling to examine how maternal emotion regulation difficulties and subclinical depression directly and indirectly, through sensitivity and postnatal bonding, assessed at 6 to 8 months predicted child outcomes at 12 to 16 months. We found that mothers’ sensitivity predicted fewer social-emotional and behavioral problems and that stronger bonding predicted fewer problems and more social-emotional competencies. Emotion regulation difficulties were significantly associated with depressive symptoms; yet, when accounting for shared variances, both factors differentially predicted less positive child outcomes such that more difficulties indirectly, through poorer bonding, predicted greater delay in competencies, and more symptoms indirectly, through less sensitivity, predicted more problems. Current findings underline the significance of maternal factors impacting the quality of mother–child interaction for children's positive development. Potential implications for early prevention programs to support children who are otherwise at risk for negative emotional outcomes due to mothers’ emotional state postpartum are discussed.     

Testing Event-Based Forms of Causality

Three fundamental types of causal relations are those of necessity, sufficiency, and necessity and sufficiency. These types are defined in contexts of categorical variables or events. Using statement calculus or Boolean algebra, one can determine which patterns of events are in support of a particular form of causal relation. In this article, we approach the analysis of these forms of causality taking the perspective of the analyst of empirical data. It is proposed using Configural Frequency Analysis (CFA) to test hypotheses about type of causal relation. Models are proposed for two-variable and multi-variable cases. Two CFA approaches are proposed. In the first, individual patterns (configurations) are examined under the question whether they are in support of a particular type of causal relation. In the second, patterns that are in support are compared with corresponding patterns that are not in support. In an empirical example, hypotheses are tested on the prediction of sustainability of change in dietary fat intake habits.