In 1974 an article appeared in Science magazine with the dry-sounding title “Judgment Under Uncertainty: Heuristics and Biases” by a pair of psychologists who were not well known outside their discipline of decision theory. In it Amos Tversky and Daniel Kahneman introduced the world to Prospect Theory, which mapped out how humans actually behave when faced with decisions about gains and losses, in contrast to how economists assumed that people behave. Prospect Theory turned Economics on its head by demonstrating through a series of ingenious experiments that people are much more concerned with losses than they are with gains, and that framing a choice from one perspective or the other will result in decisions that are exactly the opposite of each other, even if the outcomes are monetarily the same. Prospect Theory led cognitive psychology in a new direction that began to uncover other human biases in thinking that are probably not learned but are part of our brain’s wiring.

Thinking fast and slow.

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Elements Of Episodic Memory

It is regarded as best practice for psychologists to report effect size when disseminating quantitative research findings. Reporting of effect size in the psychological literature is patchy – though this may be changing – and when reported it is far from clear that appropriate effect size statistics are employed. This paper considers the practice of reporting point estimates of standardized effect size and explores factors such as reliability, range restriction and differences in design that distort standardized effect size unless suitable corrections are employed. For most purposes simple (unstandardized) effect size is more robust and versatile than standardized effect size. Guidelines for deciding what effect size metric to use and how to report it are outlined. Foremost among these are: i) a preference for simple effect size over standardized effect size, and ii) the use of confidence intervals to indicate a plausible range of values the effect might take. Deciding on the appropriate effect size statistic to report always requires careful thought and should be influenced by the goals of the researcher, the context of the research and the potential needs of readers.

/pdf/standardized-or-simple-effect-size-what-should-be-reported-15eylry44y.pdf

Standardized or simple effect size: what should be reported?

Color as a Science

Rumination, defined as repetitive thinking about negative information, has been found to lead to serious maladaptive consequences, including longer and more severe episodes of major depression. In this review, we present and discuss research findings motivated by the formulation that individual differences in cognitive processes that control how information is processed influence the likelihood that thoughts will become repetitive and negative. Several studies have demonstrated that a tendency to ruminate (i.e., trait rumination) is related to difficulties updating working memory (WM) and disengaging from and forgetting no-longer-relevant information. Other investigators have documented that trait rumination is also associated with an enhanced ability to ignore distracting information and with more stable maintenance of task-relevant information. In contrast to trait rumination, a state of rumination has been found to be related to widespread deficits in cognitive control. In this article, we discuss how the current accounts of control functioning cannot explain this pattern of anomalous control functioning. To explain these findings, including unexpected and contradictory results, we present an attentional scope model of rumination that posits that a constricted array of thoughts, percepts, and actions that are activated in WM or available for selection from long-term memory affects the control functioning of trait ruminators. This model explains, at a cognitive level, why rumination is particularly likely to arise when individuals are in a negative mood state; it also accounts for a number of findings outside of the rumination-control literature and generates several novel predictions.

An attentional scope model of rumination.

The purpose of this paper is to promote statistical power analysis in the behavioral sciences by introducing the easy to use GPower software GPower is a free general power analysis program available in two essentially equivalent versions, one designed for Macintosh OS/OS X and the other for MS‐DOS/Windows platforms Psychological research examples are presented to illustrate the various features of the GPower software In particular, a priori, post‐hoc, and compromise power analyses for t‐tests, F‐tests, and χ2‐tests will be demonstrated For all examples, the underlying statistical concepts as well as the implementation in GPower will be described In the behavioral sciences, we routinely apply statistical tests, but control of statistical power cannot be taken for granted However, neglecting statistical power—the probability of rejecting false null hypotheses—can have severe consequences For example, without control of statistical power it is very difficult to interpret nonsignificant results Statistical tests can produce nonsignificant results because (a) the null hypothesis (H0) holds and is retained correctly or (b) the alternative hypothesis (H1) holds but the test has not been powerful enough to detect the deviations from H0 Obviously, there is no reasonable way to decide between interpretations (a) and

/pdf/a-short-tutorial-of-gpower-5aszwezbpt.pdf

A short tutorial of GPower

https://scholarlypublications.universiteitleiden.nl/access/item%3A2968918/view

Binding and Retrieval in Action Control (BRAC).

. Reactions to recently ignored stimuli are slowed down or more error prone when compared to reactions to control stimuli. This so-called negative priming effect has been traditionally investigated in the area of selective attention. More recent theory developments conceptualize the negative priming effect as a memory phenomenon. This review presents four models to explain the phenomenon as well as their essential empirical evidence. The review also considers several negative priming characteristics - that is stimulus modality, prime selection and prime response requirement, probe interference, stimulus repetition, aging and thought disorders, and physiological correlates. On these bases, it is concluded that only the distractor inhibition and the episodic retrieval models have survived empirical testing so far. Whereas evidence has increased that negative priming clearly obeys memory retrieval principles, the distractor inhibition model has lost much of its persuasiveness within recent years.

https://www.psychologie.hhu.de/fileadmin/redaktion/Oeffentliche_Medien/Fakultaeten/Mathematisch-Naturwissenschaftliche_Fakultaet/Psychologie/AAP/Publikationen/2007/Mayr_Buchner__2007_.pdf

Negative Priming as a Memory Phenomenon

Four experiments are reported in which the mechanisms underlying auditory negative priming were investigated. In Experiments 1A and 1B, preprime-prime intervals and prime-probe intervals were manipulated. The ratio between the 2 intervals determined the size of the negative priming effect. Results are compatible with the episodic retrieval account, according to which the retrieval of inappropriate response information associated with the previous distractor slows down responding when that stimulus becomes the target. Experiment 2 tested a variant of this account, according to which the retrieval of the prime response rather than the retrieval of nonresponse information interferes with responding. Consistent with this variant, participants erroneously responded with the prime response more frequently in the ignored repetition condition than in the control condition. Experiment 3 replicated this finding and generalized it to the visual modality. The authors conclude that the retrieval of the inappropriate prime response is a determinant of the negative priming phenomenon.

/pdf/evidence-for-episodic-retrieval-of-inadequate-prime-18jpenz8o8.pdf

Evidence for episodic retrieval of inadequate prime responses in auditory negative priming.

Reading text from computer screens is better when text is printed in dark letters on light background (positive polarity) than when it is printed in light letters on dark background (negative polarity). An experiment is presented that tests whether this positive polarity advantage is due to the fact that overall display luminance is typically higher for positive than for negative polarity displays. To this end, text-background polarity and display luminance were manipulated independently. No positive polarity advantage was observed when overall display luminance of positive and negative polarity displays was equivalent. There was only an effect of display luminance, with better performance for the higher-luminance displays. This suggests that the positive polarity advantage is in fact due to the typically higher luminance of positive polarity displays. Readability of text presented on computer screens (e.g. on websites) is better when the overall display luminance level is high, as in positive polarity displays (dark letters on light background). Display polarity per se does not affect readability.

Susanne Mayr

Papers

A short tutorial of GPower

Binding and Retrieval in Action Control (BRAC).

Negative Priming as a Memory Phenomenon

Evidence for episodic retrieval of inadequate prime responses in auditory negative priming.

The advantage of positive text-background polarity is due to high display luminance.