Footprint of publication selection bias on meta-analyses in medicine, environmental sciences, psychology, and economics

Publication selection bias undermines the systematic accumulation of evidence. To assess the extent of this problem, we survey over 68,000 meta-analyses containing over 700,000 effect size estimates from medicine (67,386/597,699), environmental sciences (199/12,707), psychology (605/23,563), and economics (327/91,421). Our results indicate that meta-analyses in economics are the most severely contaminated by publication selection bias, closely followed by meta-analyses in environmental sciences and psychology, whereas meta-analyses in medicine are contaminated the least. After adjusting for publication selection bias, the median probability of the presence of an effect decreased from 99.9% to 29.7% in economics, from 98.9% to 55.7% in psychology, from 99.8% to 70.7% in environmental sciences, and from 38.0% to 29.7% in medicine. The median absolute effect sizes (in terms of standardized mean differences) decreased from d = 0.20 to d = 0.07 in economics, from d = 0.37 to d = 0.26 in psychology, from d = 0.62 to d = 0.43 in environmental sciences, and from d = 0.24 to d = 0.13 in medicine

Footprint of publication selection bias on meta-analyses in medicine, environmental sciences, psychology, and economics

Publication selection bias undermines the systematic accumulation of evidence. To assess the extent of this problem, we survey over 68,000 meta-analyses containing over 700,000 effect size estimates from medicine (67,386/597,699), environmental sciences (199/12,707), psychology (605/23,563), and economics (327/91,421). Our results indicate that meta-analyses in economics are the most severely contaminated by publication selection bias, closely followed by meta-analyses in environmental sciences and psychology, whereas meta-analyses in medicine are contaminated the least. After adjusting for publication selection bias, the median probability of the presence of an effect decreased from 99.9% to 29.7% in economics, from 98.9% to 55.7% in psychology, from 99.8% to 70.7% in environmental sciences, and from 38.0% to 29.7% in medicine. The median absolute effect sizes (in terms of standardized mean differences) decreased from d = 0.20 to d = 0.07 in economics, from d = 0.37 to d = 0.26 in psychology, from d = 0.62 to d = 0.43 in environmental sciences, and from d = 0.24 to d = 0.13 in medicine

Potential of Airborne LiDAR Derived Vegetation Structure for the Prediction of Animal Species Richness at Mount Kilimanjaro

The monitoring of species and functional diversity is of increasing relevance for the development of strategies for the conservation and management of biodiversity. Therefore, reliable estimates of the performance of monitoring techniques across taxa become important. Using a unique dataset, this study investigates the potential of airborne LiDAR-derived variables characterizing vegetation structure as predictors for animal species richness at the southern slopes of Mount Kilimanjaro. To disentangle the structural LiDAR information from co-factors related to elevational vegetation zones, LiDAR-based models were compared to the predictive power of elevation models. 17 taxa and 4 feeding guilds were modeled and the standardized study design allowed for a comparison across the assemblages. Results show that most taxa (14) and feeding guilds (3) can be predicted best by elevation with normalized RMSE values but only for three of those taxa and two of those feeding guilds the difference to other models is significant. Generally, modeling performances between different models vary only slightly for each assemblage. For the remaining, structural information at most showed little additional contribution to the performance. In summary, LiDAR observations can be used for animal species prediction. However, the effort and cost of aerial surveys are not always in proportion with the prediction quality, especially when the species distribution follows zonal patterns, and elevation information yields similar results

Dataset for the paper "SABCEMM - A Simulator for Agent Based Computational Economic Market Models"

This is the corresponding dataset to the publication "SABCEMM - A Simulator for Agent-Based Computational Economic Market Models" currently available at https://arxiv.org/abs/1801.01811 and submitted to the journal Computational Economics (https://link.springer.com/journal/10614).To enable other researchers to reproduce our results the code of our simulator is available at https://github.com/SABCEMM/SABCEMM. Further we publish this dataset to facilitate an open discussion about our findings.In the following we will briefly explain the data format and how the files relate to our publication

Dataset for Simulation of Stylized Facts in Agent-Based Computational Economic Market Models

This is the corresponding dataset to the publication "Simulation of Stylized Facts in Agent-Based Computational Economic Market Models" (see related paper below). To enable other researchers to reproduce our results the code of our simulator is available at https://github.com/SABCEMM/SABCEMM. Further we publish this dataset to facilitate an open discussion about our findings.In the dataset description we briefly explain the data format and how the files relate to our publication

A Self-Assembled Molecular Cage for Substrate-Selective Epoxidation Reactions in Aqueous Media

Encapsulation of a manganese porphyrin in a self-assembled molecular cage allows catalytic epoxidation of various substrates in 1:1 water/acetonitrile mixtures. The cage acts as a phase-transfer catalyst and creates a protective environment for the catalyst improving the stability. The encapsulated catalyst also allows discrimination between styrene derivatives of various sizes. In a direct competition experiment, the selectivity of the epoxidation reaction could be inverted with respect to a benchmark catalyst

Anatomical Variations of the Pectoralis Muscle and Its Importance for Breast Implant Surgery

Background:. In breast augmentation, during submuscular or dual plane dissection, anatomical variations of the inferior and costal origin of the pectoralis major muscle (PMM) play a key role to ensure optimal implant coverage. Especially, a short and narrow muscle or surgical release along the sternum increases the risk of irregularities and animation deformities of the implant. Methods:. In 84 consecutive aesthetic breast augmentations intraoperatively, measurement of PMM dimensions was performed bilaterally. These PMM measurements were then correlated with the preoperative breast width, the inframammary fold, and the placement of the implant’s lower pole. Results:. One hundred sixty-eight PMMs of 84 patients were dissected with a dual plane II or III technique for primary aesthetic breast augmentation. In 88% of breasts, the calculated implants’ lower pole was below the inferiomedial origin of the pectoralis muscle. In 10% of patients, a separation (more than 1 cm wide and 2 cm wide) in the inferior-medial origin of the PMM was noted. An asymmetry more than 0.5 cm in length between the left and right pectoralis major was noted in 36% of patients. Conclusions:. In this series, the anatomy of the PMM demonstrates a substantial variability in width and length and a considerable asymmetry in its dimensions. These findings emphasize the importance of good access and visualization of the origin of the PMM fibers before its division