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Schoenfelder, G.

Publications and source records attributed to Schoenfelder, G..

2 recordsLinked to original sources

Repeatability analysis improves the reliability of behavioral data

Reliability of data has become a major concern in the course of the reproducibility crisis. Especially when studying animal behavior, confounding factors such as novel test apparatus can lead to a wide variability of data. At worst, effects of novelty or stress related behavior can mask treatment effects and the behavioral data may be misinterpreted. Habituation to the test situation is a common practice to circumvent novelty induced increases in variance and to improve the reliability of the respective measurements. However, there is a lack of published empirical knowledge regarding reasonable habituation procedures and a method validation seems to be overdue. This study aimed at setting up a simple strategy to increase reliability of behavioral data. Therefore, exemplary data from mice tested in an Open Field (OF) arena were used to elucidate the potential of habituation and how reliability of measures can be confirmed by means of a repeatability analysis using the software R. On seven consecutive days, male C57BL/6J, BALB/cJ and 129S1/SvImJ mice were tested in an OF arena once daily and individual mouse behavior (distance travelled, average activity) was recorded. A repeatability analysis was conducted in order to estimate the reliability of measured animal behavior with regard to repeated trials of habituation. Our data analysis revealed that monitoring animal behavior during habituation is important to determine when individual differences of the measurements are stable. Here, the mixed effect model framework proved to be a powerful tool for estimating repeatability values. Repeatability values from distance travelled and average activity increased over the habituation period, revealing that around 60 % of the variance of the data can be explained by individual differences between mice. The first day of habituation was statistically significantly different from the following 6 days in terms of distance travelled and average activity. A habituation period of three days appeared to be sufficient in this study. Overall these results emphasize the importance of habituation and in depth analysis of habituation data to define the correct starting point of the experiment for improving the reliability and reproducibility of experimental data.

animal behavior and cognition↗

How Changes in Common Practice Can Improve the Quality of Biomedical Science

Assessing the impact of recommendations rectifying the reproducibility crisis (publishing both positive and \"negative\" results and increasing statistical power) on competing objectives, such as discovering causal relationships, avoiding publishing false positive results, and reducing resource consumption, we developed a new probabilistic model. Our model quantifies the impact of each single suggestion for an individual study and their relation and consequences for the entire research process. We can prove that higher-powered experiments can save resources in the overall research process without generating excess false positives. The better the quality of the pre-study information and its exploitation, the more likely this beneficial effect is to occur. Additionally, we quantify the adverse effects of neglecting good practices in the design and conduct of hypotheses-based research, and the responsibility to publish \"negative\" findings. Our contribution is a plea for adherence to or reinforcement of the good scientific practice and publication of \"negative\" findings.

scientific communication and education↗