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Nonparametric confidence distributions estimate statistical functionals by a distribution function on the parameter space, instead of the classical point or interval estimators. The concept bears analogy to the Bayesian posterior, but is nevertheless a completely frequentist concept. In order to ensure the desired statistical properties, we require that the cumulative distribution function on the parameter space is, evaluated at the true parameter, uniformly distributed over the unit interval. Our main focus lies on developing confidence distributions for the nonparametric relative effect and some natural extensions thereof. We develop asymptotic, range preserving and—especially important in the case of small sample sizes—approximate confidence distributions based on rank and pseudo-rank procedures. Due to the close relationship between point estimators, confidence intervals and p-values, these can all be approached in a unified manner within the framework of confidence distributions. The main goal of our contribution is to make the powerful theory of confidence distributions available in a nonparametric context, that is, for situations where methods relying on parametric assumptions are not justifiable. Application of the proposed methods and interpretation of the results is demonstrated using real data sets, including ordinal, non-metric data. [ABSTRACT FROM AUTHOR]

It is common in a number of disciplines such as economics, sociology, psychology and clinical trials that researchers are interested to test treatment effects among several of the outcomes in the same direction. Such tests can be performed by using equi-directional test statistics for multivariate data. If on the other hand, treatment effects with respect to one or more of the outcomes differ in direction, the power of equi-directional tests is compromised. Thus, we interchanged the signs of different outcomes by multiplying the values with - 1 and made the anticipated direction similar. Following this, we employed a recently proposed test statistic which handles equi-directional alternatives since the direction of treatment effects is made uniform through interchanging the signs. Once monotonic trend, that is, monotonic increasing for some of the outcomes and monotonic decreasing for others is demonstrated through the global test statistic, an investigator may be further interested in which specific outcomes or sets of outcomes actually these trends are observed. To address this issue, we adapted a closed testing principle. The whole procedure is illustrated by data sets from a toxicology study carried out by the National Toxicology Program, and a cost of transporting milk from farms to dairy plants per mile by different trucks. [ABSTRACT FROM AUTHOR]

In many scientific disciplines datasets contain many more variables than observational units (so-called thick data). A common hypothesis of interest in this setting is the global null hypothesis of no difference in multivariate distribution between different experimental or observational groups. Several permutation-based nonparametric tests have been proposed for this hypothesis. In this paper we investigate the potential differences in performance between different methods used to test thick data. In particular we focus on an extension of the Nonparametric combination procedure (NPC) proposed by Pesarin and Salmaso, a rank-based approach by Ellis, Burchett, Harrar and Bathke, and a distance-based approach by Mielke. The effect of different combining procedures on the NPC is also explored. Finally, we illustrate the use of these methods on a real-life dataset. [ABSTRACT FROM AUTHOR]

While it has become standard practice to report the reliability of self-report scales, it remains uncommon to do the same for experimental paradigms. To facilitate this practice, we review old and new ways to compute reliability in reaction-time tasks, and we compare their accuracy using a simulation study. Highly inaccurate and negatively biased reliability estimates are obtained through the common practice of averaging sets of trials and submitting them to Cronbach’s alpha. Much more accurate reliability estimates are obtained using split-half reliability methods, especially by computing many random split-half correlations and aggregating them in a metric known as permutation-based split-half reliability. Through reanalysis of existing data and comparison of reliability values reported in the literature, we confirm that Cronbach’s alpha also tends to be lower than split-half reliability in real data. We further establish a set of practices to maximize the accuracy of the permutation-based split-half reliability coefficient through simulations. We find that its accuracy is improved by ensuring each split-half dataset contains an approximately equal number of trials for each stimulus, by correcting the averaged correlation for test length using a modified variant of the Spearman–Brown formula, and by computing a sufficient number of split-half correlations: around 5,400 are needed to obtain a stable estimate for median-based double-difference scores computed from 30 participants and 256 trials. To conclude, we review the available software for computing this coefficient. [ABSTRACT FROM AUTHOR]

In this paper, we propose a new non-parametric test for equality of distributions. The test is based on the recently introduced measure of (niche) overlap and its rank-based estimator. As the estimator makes only one basic assumption on the underlying distribution, namely continuity, the test is universal applicable in contrast to many tests that are restricted to only specific scenarios. By construction, the new test is capable of detecting differences in location and scale. It thus complements the large class of rank-based tests that are constructed based on the non-parametric relative effect. In simulations this new test procedure obtained higher power and lower type I error compared to two common tests in several settings. The new procedure shows overall good performance. Together with its simplicity, this test can be used broadly. [ABSTRACT FROM AUTHOR]

Lecideoid lichens as dominant vegetation-forming organisms in the climatically harsh areas of the southern part of continental Antarctica show clear preferences in relation to environmental conditions (i.e. macroclimate). 306 lichen samples were included in the study, collected along the Ross Sea coast (78°S–85.5°S) at six climatically different sites. The species compositions as well as the associations of their two dominant symbiotic partners (myco- and photobiont) were set in context with environmental conditions along the latitudinal gradient. Diversity values were nonlinear with respect to latitude, with the highest alpha diversity in the milder areas of the McMurdo Dry Valleys (78°S) and the most southern areas (Durham Point, 85.5°S; Garden Spur, 84.5°S), and lowest in the especially arid and cold Darwin Area (~ 79.8°S). Furthermore, the specificity of mycobiont species towards their photobionts decreased under more severe climate conditions. The generalist lichen species Lecanora fuscobrunnea and Lecidea cancriformis were present in almost all habitats, but were dominant in climatically extreme areas. Carbonea vorticosa, Lecidella greenii and Rhizoplaca macleanii were confined to milder areas. In summary, the macroclimate is considered to be the main driver of species distribution, making certain species useful as bioindicators of climate conditions and, consequently, for assessing the consequences of climate change. [ABSTRACT FROM AUTHOR]

Summary: Background: During the second wave of the coronavirus disease 2019 (COVID-19) pandemic Austria suffered one of the highest severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) rates worldwide. We report performance parameters of a SARS-CoV‑2 screening program established for cancer outpatients at our center. Methods: Institutional policy recommended routine biweekly SARS-CoV‑2 testing. Adherence to the testing recommendation during the second wave of the COVID-19 pandemic between 1 October and 30 November 2020 was analyzed. The SARS-CoV‑2 infection rate during first wave period (21 March to 4 May 2020) was compared to the one during second wave. Results: A total of 1577 cancer patients were seen at our outpatient clinic during the second wave. In 1079/1577 (68.4%) patients, at least 1 SARS-CoV2 test was performed. Overall 2833 tests were performed, 23/1577 (1.5%, 95% confidence interval, CI 1.0–2.2%) patients were tested positive for SARS-CoV‑2, which indicates a significant increase compared to the first wave (4/1016; 0.4%, 95% CI 0.1–1.0%) with an odds ratio of 3.9 (95% CI 1.5–10.1; p < 0.005). Patients undergoing active anticancer treatment (172/960; 17.9% not tested) were more likely to have undergone a SARS-CoV‑2 test than patients in follow-up or best supportive care (326/617; 52.8% not tested p < 0.001). Furthermore, patients with only 1 visit within 4 weeks were more likely to not have undergone a SARS-CoV‑2 test (386/598; 64.5%) compared to patients with 2 or more visits (112/979; 11.4%; p < 0.001). The projected number of patients with undetected SARS-CoV‑2 infection during the study period was 5. Conclusion: We identified clinical patient parameters influencing SARS-CoV‑2 testing coverage in cancer outpatients. Our data can provide information on generation of standard operating procedures and resource allocation during subsequent infection waves. [ABSTRACT FROM AUTHOR]

Climatically extreme regions such as the polar deserts of the McMurdo Dry Valleys (78° S) in Continental Antarctica are key areas for a better understanding of changes in ecosystems. Therefore, it is particularly important to analyze and communicate current patterns of biodiversity in these sensitive areas, where precipitation mostly occurs in form of snow and liquid water is rare. Humidity provided by dew, clouds, and fog are the main water sources, especially for rock-dwelling crustose lichens as one of the most common vegetation-forming organisms. We investigated the diversity and interaction specificity of myco-/photobiont associations of 232 crustose lichen specimens, collected along an elevational gradient (171–959 m a.s.l.) within the McMurdo Dry Valleys. The mycobiont species and photobiont OTUs were identified by using three markers each (nrITS, mtSSU, RPB1, and nrITS, psbJ-L, COX2). Elevation, positively associated with water availability, turned out to be the key factor explaining most of the distribution patterns of the mycobionts. Pairwise comparisons showed Lecidea cancriformis and Rhizoplaca macleanii to be significantly more common at higher elevations and Carbonea vorticosa and Lecidea polypycnidophora at lower elevations. Lichen photobionts were dominated by the globally distributed Trebouxia OTU, Tr_A02 which occurred at all habitats. Network specialization resulting from myco-/photobiont bipartite network structure varied with elevation and associated abiotic factors. Along an elevational gradient, the spatial distribution, diversity, and genetic variability of the lichen symbionts appear to be mainly influenced by improved water relations at higher altitudes. [ABSTRACT FROM AUTHOR]

For testing the hypothesis that macroclimatological factors determine the occurrence, biodiversity, and species specificity of both symbiotic partners of Antarctic lecideoid lichens, we present a first approach for the computation of the full set of 19 BIOCLIM variables, as available at http://www.worldclim.org/ for all regions of the world with exception of Antarctica. Annual mean temperature (Bio 1) and annual precipitation (Bio 12) were chosen to define climate zones of the Antarctic continent and adjacent islands as required for ecological niche modeling (ENM). The zones are based on data for the years 2009–2015 which was obtained from the Antarctic Mesoscale Prediction System (AMPS) database of the Ohio State University. For both temperature and precipitation, two separate zonings were specified; temperature values were divided into 12 zones (named 1 to 12) and precipitation values into five (named A to E). By combining these two partitions, we defined climate zonings where each geographical point can be uniquely assigned to exactly one zone, which allows an immediate explicit interpretation. The soundness of the newly calculated climate zones was tested by comparison with already published data, which used only three zones defined on climate information from the literature. The newly defined climate zones result in a more precise assignment of species distribution to the single habitats. This study provides the basis for a more detailed continental-wide ENM using a comprehensive dataset of lichen specimens which are located within 21 different climate regions. [ABSTRACT FROM AUTHOR]

Awareness of postmortem degradation processes in a human body is fundamental to develop methods for forensic time since death estimation (TDE). Currently, applied approaches are all more or less limited to certain postmortem phases, or have restrictions on behalf of circumstances of death. Novel techniques, however, rarely exceed basic research phases due to various reasons. We report the first application of a novel method, based on decay of muscle proteins, in a recent case of murder-suicide, where other TDE methods failed to obtain data. We detected considerably different protein degradation profiles in both individuals involved and compared the data to our presently available database. We obtained statistical evidence for un-simultaneous death and therefore received valuable information to trace the progression of events based on protein degradation. Although we could not sensibly convert the data to respective times of death, this case highlights the potential for future application and elucidates the necessary further steps to develop a viable TDE method. [ABSTRACT FROM AUTHOR]

We propose a new method to make inference about an eye parameter based on data that contains measurements on both eyes for some subjects, and measurements on only one eye on the others. Subject effects are modeled as additive and random, and correlation between observations on the same subject are taken into account. We derive confidence intervals for the parameter of interest, using unbiased estimators of mean and variance, and yielding explicit formulas. The results are compared to approaches commonly used in the literature, using theoretical considerations and a simulation study. The method works well even for small to moderate sample sizes, for continuous and for discrete data, and it is applicable generally for the situation where data is collected partially in pairs and partially in singles, and inference is to be made about a common location parameter. The conclusions as to how one should best average correlated data may be surprising, and somewhat revising conventional wisdom. [ABSTRACT FROM AUTHOR]

Subjective memory impairment (SMI) is being increasingly recognized as a preclinical phase of Alzheimer disease (AD). Short latency afferent inhibition (SAI) is helpful in demonstrating dysfunction of central cholinergic circuits, and was reported to be abnormal in patients with AD and amnestic multiple domain mild cognitive impairment. In this study, we found normal SAI in 20 subjects with SMI. SAI could be a useful biomarker for identifying, among individuals with memory complaints, those in whom cholinergic degeneration has occurred. [ABSTRACT FROM AUTHOR]

In this paper, we present results for testing main, simple and interaction effects in heteroscedastic two factor MANOVA models. In particular, we suggest modifications to the MANOVA sum of squares and cross product matrices to account for heteroscedasticity. Based on these modified matrices, we define some multivariate test statistics and derive their asymptotic distributions under non-normality for the null as well as non-null cases. Derivation of these results relies on the perturbation method and limit theorems for independently distributed random matrices. Based on the asymptotic distributions, we devise small sample approximations for the quantiles of the null distributions. The numerical accuracy of the large sample as well as small sample approximations are favorable. A real data set from a Smoking Cessation Trial is analyzed to illustrate the application of the methods. [ABSTRACT FROM AUTHOR]