Comparing theories with the Ising model of explanatory coherence.

Theories are among the most important tools of science. Lewin (1943) already noted "There is nothing as practical as a good theory." Although psychologists discussed problems of theory in their discipline for a long time, weak theories are still widespread in most subfields. One possible reason for this is that psychologists lack the tools to systematically assess the quality of their theories. Thagard (1989) developed a computational model for formal theory evaluation based on the concept of explanatory coherence. However, there are possible improvements to Thagard's (1989) model and it is not available in software that psychologists typically use. Therefore, we developed a new implementation of explanatory coherence based on the Ising model. We demonstrate the capabilities of this new Ising model of Explanatory Coherence (IMEC) on several examples from psychology and other sciences. In addition, we implemented it in the R-package IMEC to assist scientists in evaluating the quality of their theories in practice. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

A Bayesian perspective on severity: risky predictions and specific hypotheses.

A tradition that goes back to Sir Karl R. Popper assesses the value of a statistical test primarily by its severity: was there an honest and stringent attempt to prove the tested hypothesis wrong? For "error statisticians" such as Mayo (1996, 2018), and frequentists more generally, severity is a key virtue in hypothesis tests. Conversely, failure to incorporate severity into statistical inference, as allegedly happens in Bayesian inference, counts as a major methodological shortcoming. Our paper pursues a double goal: First, we argue that the error-statistical explication of severity has substantive drawbacks; specifically, the neglect of research context and the specificity of the predictions of the hypothesis. Second, we argue that severity matters for Bayesian inference via the value of specific, risky predictions: severity boosts the expected evidential value of a Bayesian hypothesis test. We illustrate severity-based reasoning in Bayesian statistics by means of a practical example and discuss its advantages and potential drawbacks.

Monocyte response after colorectal surgery: A prospective cohort study.

Background: Tumor resection is the common approach in patients with colorectal malignancy. Profound insight into inflammatory changes that accompany the normal post-operative stress response will establish reference parameters useful for identification of putative complications. Alterations in circulating monocytes might be indicative as these cells are considered to be the most responsive leukocytes to trauma. Therefore, the aim of this study is to assess the monocyte subset kinetic and phenotypic changes in response to surgery. Methods: Fifty patients undergoing colorectal tumor resection were included in a multicenter prospective cohort study. Blood samples were collected early in the morning prior to surgery and the next days through postoperative day three for flowcytometric analysis. Leukocyte subtypes were identified and expression of activation stage-related markers by monocyte subsets was quantified. Results: Changes in leukocyte subset composition and monocyte subset phenotypes were most prominent at the first day postoperatively, after which these parameters typically returned to normal or near-normal preoperative values. The immunophenotypic alterations after surgery were most notable in classical and intermediate monocytes. These included up-regulation of activation markers CD64 and CD62L, but down-regulation of HLA-DR and CD54. Markers of de-activation, CD163 and CD206, were consistently increasingly expressed. Discussion/conclusion: The current study gives detailed insight into the peripheral blood leukocyte response after colorectal cancer surgery. This form of short-term stress induces a rapid and significant redistribution of immune cells. Immunophenotypic alterations in monocytes as a response to surgery suggest a mixed profile of cellular activation and de-activation.

Objectivity for the research worker.

In the last decade, many problematic cases of scientific conduct have been diagnosed; some of which involve outright fraud (e.g., Stapel, 2012) others are more subtle (e.g., supposed evidence of extrasensory perception; Bem, 2011). These and similar problems can be interpreted as caused by lack of scientific objectivity. The current philosophical theories of objectivity do not provide scientists with conceptualizations that can be effectively put into practice in remedying these issues. We propose a novel way of thinking about objectivity for individual scientists; a negative and dynamic approach.We provide a philosophical conceptualization of objectivity that is informed by empirical research. In particular, it is our intention to take the first steps in providing an empirically and methodologically informed inventory of factors that impair the scientific practice. The inventory will be compiled into a negative conceptualization (i.e., what is not objective), which could in principle be used by individual scientists to assess (deviations from) objectivity of scientific practice. We propose a preliminary outline of a usable and testable instrument for indicating the objectivity of scientific practice.

Seven steps toward more transparency in statistical practice.

We argue that statistical practice in the social and behavioural sciences benefits from transparency, a fair acknowledgement of uncertainty and openness to alternative interpretations. Here, to promote such a practice, we recommend seven concrete statistical procedures: (1) visualizing data; (2) quantifying inferential uncertainty; (3) assessing data preprocessing choices; (4) reporting multiple models; (5) involving multiple analysts; (6) interpreting results modestly; and (7) sharing data and code. We discuss their benefits and limitations, and provide guidelines for adoption. Each of the seven procedures finds inspiration in Merton's ethos of science as reflected in the norms of communalism, universalism, disinterestedness and organized scepticism. We believe that these ethical considerations-as well as their statistical consequences-establish common ground among data analysts, despite continuing disagreements about the foundations of statistical inference.

Consensus-based guidance for conducting and reporting multi-analyst studies.

Any large dataset can be analyzed in a number of ways, and it is possible that the use of different analysis strategies will lead to different results and conclusions. One way to assess whether the results obtained depend on the analysis strategy chosen is to employ multiple analysts and leave each of them free to follow their own approach. Here, we present consensus-based guidance for conducting and reporting such multi-analyst studies, and we discuss how broader adoption of the multi-analyst approach has the potential to strengthen the robustness of results and conclusions obtained from analyses of datasets in basic and applied research.

Moderate Contrast in the Evaluation of Paintings Is Liked More but Remembered Less than High Contrast.

Many visual aspects of paintings, as well as exposure to art and cultural norms, contribute to the aesthetic evaluation of paintings. The current study looked at heightened visual contrast as an important factor in the appreciation of paintings. Participants evaluated abstract digitized paintings that were manipulated in contrast for an appreciation task and were later presented with these paintings in a memory task. The results indicated that for art appreciation, a moderate increase in contrast resulted in the highest appreciation for paintings whereas recognition memory was better for paintings with a higher increase in contrast. These results replicate earlier findings with regard to the role of contrast in aesthetic perception and extend these findings by demonstrating a surprising different effect of contrast manipulation for recognition memory. Confidence with which memory decisions were made was in line with art appreciation decisions not memory performance.

Implicit emotion regulation in the context of viewing artworks: ERP evidence in response to pleasant and unpleasant pictures.

Presenting affective pictures as a work of art could change perceivers' judgment and strength in emotional reactions. Aesthetic theory states that perceivers of art emotionally distance themselves, allowing them to appreciate works of art depicting gruesome events. To examine whether implicit emotion regulation is induced by an art context, we assessed whether presenting pleasant and unpleasant IAPS pictures as either "works of art comprising paintings, digital renderings, and photographs of staged scenes" or "photographs depicting real events" modulated perceivers' Late Positive Potentials (LPP) and likability ratings. In line with previous research and aesthetic theory, participants evaluated the IAPS pictures as more likable when they were presented as works of art than when they were presented as photographs. Moreover, participants' late LPP amplitudes (600-900ms post picture onset) in response to the pictures were attenuated in the art context condition. These results provide evidence for an implicit emotion regulation induced by the art context.