Lower level mediation in multilevel models

Multilevel models are increasingly used to estimate models for hierarchical and repeated measures data. The authors discuss a model in which there is mediation at the lower level and the mediational links vary randomly across upper level units. One repeated measures example is a case in which a person's daily stressors affect his or her coping efforts, which affect his or her mood, and both links vary randomly across persons. Where there is mediation at the lower level and the mediational links vary randomly across upper level units, the formulas for the indirect effect and its standard error must be modified to include the covariance between the random effects. Because no standard method can estimate such a model, the authors developed an ad hoc method that is illustrated with real and simulated data. Limitations of this method and characteristics of an ideal method are discussed.     

Context and Perceptual Salience Influence the Formation of Novel Stereotypes via Cumulative Cultural Evolution

We use a transmission chain method to establish how context and category salience influence the formation of novel stereotypes through cumulative cultural evolution. We created novel alien targets by combining features from three category dimensions—color, movement, and shape—thereby creating social targets that were individually unique but that also shared category membership with other aliens (e.g., two aliens might be the same color and shape but move differently). At the start of the transmission chains each alien was randomly assigned attributes that described it (e.g., arrogant, caring, confident). Participants were given training on the alien‐attribute assignments and were then tested on their memory for these. The alien‐attribute assignments participants produced during test were used as the training materials for the next participant in the transmission chain. As information was repeatedly transmitted an increasingly simplified, learnable stereotype‐like structure emerged for targets who shared the same color, such that by the end of the chains targets who shared the same color were more likely to share the same attributes (a reanalysis of data from Martin et al., 2014 which we term Experiment 1). The apparent bias toward the formation of novel stereotypes around the color category dimension was also found for objects (Experiment 2). However, when the category dimension of color was made less salient, it no longer dominated the formation of novel stereotypes (Experiment 3). The current findings suggest that context and category salience influence category dimension salience, which in turn influences the cumulative cultural evolution of information.     

The Social Relations Model: How to Understand Dyadic Processes

The social relations model (SRM) is an intriguing tool both to conceptualize and to analyze dyadic processes. We begin with explaining why interpersonal phenomena in everyday life are more complex than often considered. We then show how the SRM accounts for these complexities by decomposing interpersonal perceptions and behaviors into three independent components and describe the designs required to investigate these components. We then provide a step-by-step introduction into social relations analyses, thereby showing how the SRM can be used to investigate a multitude of exciting research questions. Finally, we summarize the existing software solutions for conducting social relations analyses. Resources for further information are suggested.     

When bias and insecurity promote accuracy: mean-level bias and tracking accuracy in couples' conflict discussions

Heterosexual couples (N = 57) discussed features about each other they wanted to change. During a review of their recorded discussions, for each 30 s of interaction, perceivers provided judgments of their partner's regard, and partners reported their actual regard for the perceiver. The authors simultaneously assessed the extent to which perceivers' over- or underestimated their partner's regard (mean-level bias) and tracked their partner's changing regard across the discussion (tracking accuracy). Perceivers on average tended to underestimate their partner's regard (negative mean-level bias) but exhibited substantial tracking accuracy. Bias and accuracy were related; perceivers that were more negatively biased more accurately tracked changes in their partner's regard. Women who were more insecure about their partner's continued regard demonstrated more negative mean-level bias and greater tracking accuracy, whereas more secure women demonstrated more positive bias and lower accuracy. The results indicate that bias and accuracy are shaped by context-relevant goals and motives.     

DataToText: A Consumer-Oriented Approach to Data Analysis

DataToText is a project developed where the user communicates the relevant information for an analysis and DataToText computer routine produces text output that describes in words, tables, and figures the results from the analyses. Two extended examples are given, one an example of a moderator analysis and the other an example of a dyadic data analysis. The advantages and disadvantages of DataToText are discussed in terms of the statement of the problem, the steps in the analysis, and understanding the meaning of the results. Also discussed is the potential role of DataToText in pedagogy. Although there are some clear deficiencies in a DataToText analysis, it is argued that, more often than not, DataToText will lead to better analyses. Finally, a call is made for methodologists to become more consumer oriented by providing researchers with tools to facilitate the use of methodological developments.     

On the ups and downs of emotion: testing between conceptual-metaphor and polarity accounts of emotional valence–spatial location interactions

In the past decade, many studies have focused on the relationship between emotional valence and vertical spatial positions from a processing perspective. Lakoff and Johnson’s (1980) work on conceptual metaphor has traditionally motivated these investigations, but recent work (Lakens in J Exp Psychol: Learn, Mem Cogn, 38: 726–736, 2012) has suggested that polarity-based perspectives offer an alternative account of response time patterns. We contrasted the predictions of these two theories using a new facial emotion recognition task, in which participants made speeded responses to happy or sad faces on a display, with the spatial location of those faces being manipulated. In three experiments (two-alternative forced choice tasks and a go/no-go task), we found a pattern of responses consistent with a polarity-based account, but inconsistent with key predictions of the conceptual-metaphor account. Overall, congruency effects were observed for positively valenced items, but not for negatively valenced items. These findings demonstrate that polarity effects extend to nonlinguistic stimuli and beyond two-alternative forced choice tasks. We discuss the results in terms of common-coding approaches to task–response mappings.     

Reflections on the actor–partner interdependence model

The actor–partner interdependence model (APIM) has been widely successful and has become the default method for analyses of dyadic data in which both members of the pair have the same measurements. This article reviews the history of the development of the APIM, focusing on the original presentation of the model, a 1979 article by Kraemer and Jacklin. Also discussed are the topics of APIM patterns, whether the APIM is a dyadic model, and the automation of APIM analyses. Although the APIM is the most popular method for dyadic analysis, it should be recognized there are alternatives that should also be considered.