Many psychological scientists and behavioral neuroscientists affirm that “emotion” influences thinking, decision-making, actions, social relationships, well-being, and physical and mental health. Yet there is no consensus on a definition of the word “emotion,” and the present data suggest that it cannot be defined as a unitary concept. Theorists and researchers attribute quite different yet heuristic meanings to “emotion.” They show considerable agreement about emotion activation, functions, and regulation. The central goal of this article is to alert researchers, students, and other (...) consumers of “emotion” research to the multiple meanings or aspects that distinguished scientists attribute to ”emotion,” increase appreciation of its interesting and challenging complexity, and sharpen perspectives on “emotion” and the associated body of literature that is of critical significance to science and society. (shrink)

A clever argument purports to show that we can directly perceive the emotions of others: (1) some emotional expressions are parts of the emotions they express; (2) perceiving a part of something is sufficient for perceiving the whole; (3) therefore, perceiving some emotional expressions is sufficient for perceiving the emotions they express. My aim in this paper is to assess the extent to which contemporary psychological theories of emotion support the first premise of this argument.

Emotions are viewed as having evolved through their adaptive value in dealing with fundamental life-tasks. Each emotion has unique features: signal, physiology, and antecedent events. Each emotion also has characteristics in common with other emotions: rapid onset, short duration, unbidden occurrence, automatic appraisal, and coherence among responses. These shared and unique characteristics are the product of our evolution, and distinguish emotions from other affective phenomena.

Several researchers have recently argued that p values lose their meaning in exploratory analyses due to an unknown inflation of the alpha level (e.g., Nosek & Lakens, 2014; Wagenmakers, 2016). For this argument to be tenable, the familywise error rate must be defined in relation to the number of hypotheses that are tested in the same study or article. Under this conceptualization, the familywise error rate is usually unknowable in exploratory analyses because it is usually unclear how many hypotheses have (...) been tested on a spontaneous basis and then omitted from the final research report. In the present article, I argue that it is inappropriate to conceptualize the familywise error rate in relation to the number of hypotheses that are tested. Instead, it is more appropriate to conceptualize familywise error in relation to the number of different tests that are conducted on the same null hypothesis in the same study. Under this conceptualization, alpha level adjustments in exploratory analyses are (a) less necessary and (b) objectively verifiable. As a result, p values do not lose their meaning in exploratory analyses. (shrink)