One-way layouts, i.e., a single factor with several levels and multiple observations at each level, frequently arise in various fields. Usually not only a global hypothesis is of interest but also multiple comparisons between the different treatment levels. In most practical situations, the distribution of observed data is unknown and there may exist a number of atypical measurements and outliers. Hence, use of parametric and semiparametric procedures that impose restrictive distributional assumptions on observed samples becomes questionable. This, in turn, emphasizes the demand on statistical procedures that enable us to accurately and reliably analyze one-way layouts with minimal conditions on available data. Nonparametric methods offer such a possibility and thus become of particular practical importance. In this article, we introduce a new R package nparcomp which provides an easy and user-friendly access to rank-based methods for the analysis of unbalanced one-way layouts. It provides procedures performing multiple comparisons and computing simultaneous confidence intervals for the estimated effects which can be easily visualized. The special case of two samples, the nonparametric Behrens-Fisher problem, is included. We illustrate the implemented procedures by examples from biology and medicine.

4D PC MR imaging allows for a detailed assessment of CSF flow dynamics helping to distinguish physiological from complex pathological flow patterns at the craniocervical junction and the cervical spine.

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Climate change in Arctic ecosystems fosters permafrost thaw and makes massive amounts of ancient soil organic carbon (OC) available to microbial breakdown. However, fractions of the organic matter (OM) may be protected from rapid decomposition by their association with minerals. Little is known about the effects of mineral-organic associations (MOA) on the microbial accessibility of OM in permafrost soils and it is not clear which factors control its temperature sensitivity. In order to investigate if and how permafrost soil OC turnover is affected by mineral controls, the heavy fraction (HF) representing mostly MOA was obtained by density fractionation from 27 permafrost soil profiles of the Siberian Arctic. In parallel laboratory incubations, the unfractionated soils (bulk) and their HF were comparatively incubated for 175 days at 5 and 15°C. The HF was equivalent to 70 ± 9% of the bulk CO respiration as compared to a share of 63 ± 1% of bulk OC that was stored in the HF. Significant reduction of OC mineralization was found in all treatments with increasing OC content of the HF (HF-OC), clay-size minerals and Fe or Al oxyhydroxides. Temperature sensitivity (Q10) decreased with increasing soil depth from 2.4 to 1.4 in the bulk soil and from 2.9 to 1.5 in the HF. A concurrent increase in the metal-to-HF-OC ratios with soil depth suggests a stronger bonding of OM to minerals in the subsoil. There, the younger C signature in CO than that of the OC indicates a preferential decomposition of the more recent OM and the existence of a MOA fraction with limited access of OM to decomposers. These results indicate strong mineral controls on the decomposability of OM after permafrost thaw and on its temperature sensitivity. Thus, we here provide evidence that OM temperature sensitivity can be attenuated by MOA in permafrost soils.

Previous European guidance for environmental risk assessment of genetically modified plants emphasized the concepts of statistical power but provided no explicit requirements for the provision of statistical power analyses. Similarly, whilst the need for good experimental designs was stressed, no minimum guidelines were set for replication or sample sizes. Furthermore, although substantial equivalence was stressed as central to risk assessment, no means of quantification of this concept was given. This paper suggests several ways in which existing guidance might be revised to address these problems. One approach explored is the 'bioequivalence' test, which has the advantage that the error of most concern to the consumer may be set relatively easily. Also, since the burden of proof is placed on the experimenter, the test promotes high-quality, well-replicated experiments with sufficient statistical power. Other recommendations cover the specification of effect sizes, the choice of appropriate comparators, the use of positive controls, meta-analyses, multivariate analysis and diversity indices. Specific guidance is suggested for experimental designs of field trials and their statistical analyses. A checklist for experimental design is proposed to accompany all environmental risk assessments.