Schizotypy, neuroticism, and saccadic eye movements: New data and meta-analysis.

Deficits on saccade tasks, particularly antisaccade performance, have been reliably reported in schizophrenia. However, less evidence is available on saccade performance in relation to schizotypy, a personality constellation harboring risk for schizophrenia. Here, we report a large empirical study of the associations of schizotypy and neuroticism with antisaccade and prosaccade performance (Study I). Additionally, we carried out meta-analyses of the association between schizotypy and antisaccade error rate (Study II). In Study I, N = 526 healthy individuals from the general population aged 18-54 years completed prosaccade and antisaccade tasks as well as the Schizotypal Personality Questionnaire (SPQ). Schizotypy was significantly associated with increased antisaccade error rate, with the disorganized dimension emerging as strongest predictor (ß = .118, p = .007). Neuroticism emerged as a significant predictor for prosaccade gain (ß = .103, p = .023) and antisaccade latency (ß = .101, p = .025). In Study II, random-effects meta-analyses were performed on the published data and those from Study I. Meta-analyses revealed significant associations (all p ≤ .003) of antisaccade error rate with positive (g = 0.37), negative (g = 0.26), disorganized (g = 0.36) and overall schizotypy (g = 0.37). Overall, the present work replicates the association between antisaccade direction errors and schizotypy. Significant findings from meta-analyses provide further evidence of the antisaccade error rate as a putative schizophrenia spectrum marker.

Does it actually feel right? A replication attempt of the rounded price effect.

How does the roundedness of prices affect product evaluations? The 'rounded price effect' postulates that depending on the context, rounded or non-rounded prices increase the purchase likelihood of consumers. The study presented here is a replication attempt of these findings and the proposed mediation of the effect through a sense of 'feeling right' when evaluating the product. p-Curve analysis and the R-Index are used to assess the robustness of the originally reported statistics since original data were not available. A pre-registered replication of study 5 from the original article was conducted in a sample of N=588 participants. For both the original product and one alternative product neither an interaction between price roundedness and context, nor a mediation through 'a sense of feeling right' was found. Our results suggest that the effect is either smaller than originally reported or contingent on other, not investigated factors. Further studies might investigate contingencies in larger samples.

Making 'null effects' informative: statistical techniques and inferential frameworks.

Being able to interpret 'null effects?is important for cumulative knowledge generation in science. To draw informative conclusions from null-effects, researchers need to move beyond the incorrect interpretation of a non-significant result in a null-hypothesis significance test as evidence of the absence of an effect. We explain how to statistically evaluate null-results using equivalence tests, Bayesian estimation, and Bayes factors. A worked example demonstrates how to apply these statistical tools and interpret the results. Finally, we explain how no statistical approach can actually prove that the null-hypothesis is true, and briefly discuss the philosophical differences between statistical approaches to examine null-effects. The increasing availability of easy-to-use software and online tools to perform equivalence tests, Bayesian estimation, and calculate Bayes factors make it timely and feasible to complement or move beyond traditional null-hypothesis tests, and allow researchers to draw more informative conclusions about null-effects. RELEVANCE FOR PATIENTS: Conclusions based on clinical trial data often focus on demonstrating differences due to treatments, despite demonstrating the absence of differences is an equally important statistical question. Researchers commonly conclude the absence of an effect based on the incorrect use of traditional methods. By providing an accessible overview of different approaches to exploring null-results, we hope researchers improve their statistical inferences. This should lead to a more accurate interpretation of studies, and facilitate knowledge generation about proposed treatments.