770 research outputs found

    Simultaneous Inference in General Parametric Models

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    Simultaneous inference is a common problem in many areas of application. If multiple null hypotheses are tested simultaneously, the probability of rejecting erroneously at least one of them increases beyond the pre-specified significance level. Simultaneous inference procedures have to be used which adjust for multiplicity and thus control the overall type I error rate. In this paper we describe simultaneous inference procedures in general parametric models, where the experimental questions are specified through a linear combination of elemental model parameters. The framework described here is quite general and extends the canonical theory of multiple comparison procedures in ANOVA models to linear regression problems, generalized linear models, linear mixed effects models, the Cox model, robust linear models, etc. Several examples using a variety of different statistical models illustrate the breadth of the results. For the analyses we use the R add-on package multcomp, which provides a convenient interface to the general approach adopted here

    A robust procedure for comparing multiple means under heteroscedasticity in unbalanced designs.

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    Investigating differences between means of more than two groups or experimental conditions is a routine research question addressed in biology. In order to assess differences statistically, multiple comparison procedures are applied. The most prominent procedures of this type, the Dunnett and Tukey-Kramer test, control the probability of reporting at least one false positive result when the data are normally distributed and when the sample sizes and variances do not differ between groups. All three assumptions are non-realistic in biological research and any violation leads to an increased number of reported false positive results. Based on a general statistical framework for simultaneous inference and robust covariance estimators we propose a new statistical multiple comparison procedure for assessing multiple means. In contrast to the Dunnett or Tukey-Kramer tests, no assumptions regarding the distribution, sample sizes or variance homogeneity are necessary. The performance of the new procedure is assessed by means of its familywise error rate and power under different distributions. The practical merits are demonstrated by a reanalysis of fatty acid phenotypes of the bacterium Bacillus simplex from the "Evolution Canyons" I and II in Israel. The simulation results show that even under severely varying variances, the procedure controls the number of false positive findings very well. Thus, the here presented procedure works well under biologically realistic scenarios of unbalanced group sizes, non-normality and heteroscedasticity

    Lattice fence and hedge barriers around an apiary increase honey bee flight height and decrease stings to people nearby

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    Urban beekeeping is becoming more popular in the UK. One of the challenges faced by urban beekeepers is finding a suitable apiary location. Honey bees are often perceived as a nuisance, mainly due to their stinging behaviour. Here, we experimentally test the assumption that barriers around an apiary such as walls or fences, force the bees to fly above human height, thereby reducing collisions with people and, consequently, stinging. The experiment was conducted in two apiaries using two common types of barrier: a lattice fence (trellis) and hedge. Barriers were 2 m high, which is taller than > 99% of humans and is also the maximum height allowed by UK planning regulations for garden fences or walls. We found that barriers were effective at both raising the mean honey bee flight height and reducing stinging. However, the effects were only seen when the barrier had been in place for a few days, not immediately after the barrier was put in place. Although this raises interesting questions regarding honey bee navigation and memory, it is not a problem for beekeepers, as any barrier placed around an apiary will be permanent. The effect of the barriers on raising bee flight height to a mean of c. 2.2-2.5 m was somewhat weak and inconsistent, probably because the bees flew high, mean of c. 1.6-2.0 m, even in the absence of a barrier. As barriers can also reduce wind exposure, improve security and are inexpensive, we recommend their use around urban apiaries in places such as private gardens or allotments, where nuisance to humans is likely to be a problem

    Hemiparasitic plant impacts animal and plant communities across four trophic levels

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    1.Understanding the impact of species on community structure is a fundamental question in ecology. There is a growing body of evidence that suggests that both sub-dominant species and parasites can have a disproportionately large impact. 2.Here we report the impacts of an organism that is both subdominant and parasitic, the hemiparasite Rhinanthus minor. Whilst the impact of parasitic angiosperms on their hosts and, to a lesser degree, co-existing plant species, have been well characterized, much less is known about their impacts on higher trophic levels. 3.We experimentally manipulated field densities of the hemiparasite Rhinanthus minor in a species rich grassland, comparing the plant and invertebrate communities in plots where it was removed, at natural densities or at enhanced densities. 4.Plots with natural and enhanced densities of R. minor had lower plant biomass than plots without the hemiparasite, but enhanced densities almost doubled the abundance of invertebrates within the plots across all trophic levels, with effects evident in herbivores, predators and detritivores. 5.The hemiparasite R. minor, despite being a sub-dominant and transient component within plant communities that it inhabits, has profound effects on four different trophic levels. These effects persist beyond the life of the hemiparasite, emphasizing its role as a keystone species in grassland communitie

    BOLD and its connection to dopamine release in human striatum: a cross-cohort comparison

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    Activity in midbrain dopamine neurons modulates the release of dopamine in terminal structures including the striatum, and controls reward-dependent valuation and choice. This fluctuating release of dopamine is thought to encode reward prediction error (RPE) signals and other value-related information crucial to decision-making, and such models have been used to track prediction error signals in the striatum as encoded by BOLD signals. However, until recently there have been no comparisons of BOLD responses and dopamine responses except for one clear correlation of these two signals in rodents. No such comparisons have been made in humans. Here, we report on the connection between the RPE-related BOLD signal recorded in one group of subjects carrying out an investment task, and the corresponding dopamine signal recorded directly using fast-scan cyclic voltammetry in a separate group of Parkinson's disease patients undergoing DBS surgery while performing the same task. The data display some correspondence between the signal types; however, there is not a one-to-one relationship. Further work is necessary to quantify the relationship between dopamine release, the BOLD signal and the computational models that have guided our understanding of both at the level of the striatum.This article is part of the themed issue 'Interpreting BOLD: a dialogue between cognitive and cellular neuroscience'
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