Multiple contrast tests with repeated and multiple endpoints : with biological applications

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Boxplots for grouped and clustered data in toxicology

The vast majority of toxicological papers summarize experimental data as bar charts of means with error bars. While these graphics are easy to generate, they often obscure essential features of the data, such as outliers or subgroups of individuals reacting differently to a treatment. In particular, raw values are of prime importance in toxicology; therefore, we argue they should not be hidden in messy supplementary tables but rather unveiled in neat graphics in the results section. We propose jittered boxplots as a very compact yet comprehensive and intuitively accessible way of visualizing grouped and clustered data from toxicological studies together with individual raw values and indications of statistical significance. A web application to create these plots is available online

Simultaneous comparisons of treatments at multiple time points: combined marginal models versus joint modeling

We discuss several aspects of multiple inference in longitudinal settings, focusing on many-to-one and all-pairwise comparisons of (a) treatment groups simultaneously at several points in time, or (b) time points simultaneously for several treatments. We assume a continuous endpoint that is measured repeatedly over time and contrast two basic modeling strategies: fitting a joint model across all occasions (with random effects and/or some residual covariance structure to account for heteroscedasticity and serial dependence), and a novel approach combining a set of simple marginal, i.e. occasion-specific models. Upon parameter and covariance estimation with either modeling approach, we employ a variant of multiple contrast tests that acknowledges correlation between time points and test statistics. This method provides simultaneous confidence intervals and adjusted p-values for elementary hypotheses as well as a global test decision. We compare via simulation the powers of multiple contrast tests based on a joint model and multiple marginal models, respectively, and quantify the benefit of incorporating longitudinal correlation, i.e. the advantage over Bonferroni. Practical application is illustrated with data from a clinical trial on bradykinin receptor antagonism

Bayesian clinical trial designs : Another option for trauma trials?

The UK-REBOA Trial is funded by the National Institute for Health Research (NIHR) Health Technology Assessment (HTA) programme (project number 14/199/09). PP was supported by the MRC Network of Hubs for Trials Methodology Research (MR/L004933/1-R/N/P/B1).Peer reviewedPublisher PD

Brassica napus L. cultivars show a broad variability in their morphology, physiology and metabolite levels in response to sulfur limitations and to pathogen attack

Under adequate sulfur supply, plants accumulate sulfate in the vacuoles and use sulfur-containing metabolites as storage compounds. Under sulfur-limiting conditions, these pools of stored sulfur-compounds are depleted in order to balance the nitrogen to sulfur ratio for protein synthesis. Stress conditions like sulfur limitation and/or pathogen attack induce changes in the sulfate pool and the levels of sulfur-containing metabolites, which often depend on the ecotypes or cultivars. We are interested in investigating the influence of the genetic background of canola (Brassica napus) cultivars in sulfur-limiting conditions on the resistance against Verticillium longisporum. Therefore, four commercially available B. napus cultivars were analyzed. These high-performing cultivars differ in some characteristics described in their cultivar pass, such as several agronomic traits, differences in the size of the root system, and resistance to certain pathogens, such as Phoma and Verticillium. The objectives of the study were to examine and explore the patterns of morphological, physiological and metabolic diversity in these B. napus cultivars at different sulfur concentrations and in the context of plant defense. Results indicate that the root systems are influenced differently by sulfur deficiency in the cultivars. Total root dry mass and length of root hairs differ not only among the cultivars but also vary in their reaction to sulfur limitation and pathogen attack. As a sensitive indicator of stress, several parameters of photosynthetic activity determined by PAM imaging showed a broad variability among the treatments. These results were supported by thermographic analysis. Levels of sulfur-containing metabolites also showed large variations. The data were interrelated to predict the specific behavior during sulfur limitation and/or pathogen attack. Advice for farming are discussed

Common pitfalls when testing additivity of treatment mixtures with chi-square analyses

Studying interactions of multiple pesticides applied simultaneously in a mixture is a common task in phytopathology. Statistical methods are employed to test whether the treatment components influence each other's efficacy in a promotive or inhibitory way (synergistic or antagonistic interaction) or rather act independent of one another (additivity). The trouble is that widely used procedures based on chi-square tests are often seriously flawed, either because people apply them in a preposterous way or because the method simply does not fit the problem at hand. Browsing recent volumes of entomological journals, we found that numerous researchers have (in all likelihood unwittingly) analysed their data as if they had had a sample size of 100 or, equally bad, a sample size of one! We show how to avoid such poor practices and further argue that chi-square testing is, even if applied correctly (meaning that no technical errors are made), a limited purpose tool for assessing treatment interactions

The R package MAMS for designing multi-arm multi-stage clinical trials

In the early stages of drug development there is often uncertainty about the most promising among a set of different treatments, different doses of the same treatment, or combinations of treatments. Multi-arm multi-stage (MAMS) clinical studies provide an efficient solution to determine which intervention is most promising. In this paper we discuss the R package MAMS that allows designing such studies within the group-sequential framework. The package implements MAMS studies with normal, binary, ordinal, or time-to-event endpoints in which either the single best treatment or all promising treatments are continued at the interim analyses. Additionally unexpected design modifications can be accounted for via the use of the conditional error approach. We provide illustrative examples of the use of the package based on real trial designs

Analysis of means:a generalized approach using R

Papers on the analysis of means (ANOM) have been circulating in the quality control literature for decades, routinely describing it as a statistical stand-alone concept. Therefore we clarify that ANOM should rather be regarded as a special case of a much more universal approach known as multiple contrast tests (MCTs). Perceiving ANOM as a grand-mean-type MCT paves the way for implementing it in the opensource software R. We give a brief tutorial on how to exploit R's versatility and introduce R package ANOM for drawing the familiar decision charts. Beyond that, we illustrate two practical aspects of data analysis with ANOM: rstly, we compare merits and drawbacks of ANOM-type MCTs and ANOVA F-test and assess their respective statistical powers, and secondly, we show that the benet of using critical values from multivariate t-distributions for ANOM instead of simple Bonferroni quantiles is oftentimes negligible

Systemic slow-release neem formulations: the future of cabbage aphids, Brevicoryne brassicae control

The efficacy and dose-response, residual effect, and effect on the fecundity of neem formulations on cabbage aphid Brevicoryne brassicae applied systemically through root tissues of Brussels sprouts (Brassica oleracea), were studied in the greenhouse. Two formulations were tested; NeemAzal granules containing 7% azadirachtin (AZA), at 75, 150, 225 and 300 mg per kilogram of the substrate and a water-based formulation, NeemAzal-T (1% AZA) at 1, 1.5, 2 and 2.5 ml/kg of substrate. The efficacy of the neem formulations was dose-dependent, with the highest doses of NeemAzal granules and NeemAzal T, (300 mg and 2.5 ml/kg of substrate) respectively, having up to 0% survival of aphids by 14 days after treatment. The manufacturer’s recommended doses, NeemAzal granules at 150 mg and NeemAzal-T at 1 ml/kg of substrate, were used to evaluate the persistence and bioresidual effect of the azadirachtin on cabbage aphid over time. After treatments, plants were infested with one-day-old aphid larvae on the same day (D0), three days (D4) and eight days (D8) after treatment. There was a sharp decrease in persistence with NeemAzal-T when plants were infested 8 days after treatment, and there was no significant difference in the survival of aphids with control plants. However, there were no differences in the survival rate of cabbage aphid larvae if exposed 0, 4 or 8 days after treatment with NeemAzal granules but the survival rate was significantly lower compared to that in the control. The fecundity of aphids decreased significantly after the application of azadirachtin. In conclusion, results show high efficacy of soil-applied NeemAzal against cabbage aphid, with NeemAzal granules, which is a slow-release formulation, giving the longest period of bioactivity hence offering the longest period of protection

Quantitative expression analysis in Brassica napus by Northern blot analysis and reverse transcription-quantitative PCR in a complex experimental setting

Analysis of gene expression is one of the major ways to better understand plant reactions to changes in environmental conditions. The comparison of many different factors influencing plant growth challenges the gene expression analysis for specific gene-targeted experiments, especially with regard to the choice of suitable reference genes. The aim of this study is to compare expression results obtained by Northern blot, semi-quantitative PCR and RT-qPCR, and to identify a reliable set of reference genes for oilseed rape (Brassica napus L.) suitable for comparing gene expression under complex experimental conditions. We investigated the influence of several factors such as sulfur deficiency, different time points during the day, varying light conditions, and their interaction on gene expression in oilseed rape plants. The expression of selected reference genes was indeed influenced under these conditions in different ways. Therefore, a recently developed algorithm, called GrayNorm, was applied to validate a set of reference genes for normalizing results obtained by Northern blot analysis. After careful comparison of the three methods mentioned above, Northern blot analysis seems to be a reliable and cost-effective alternative for gene expression analysis under a complex growth regime. For using this method in a quantitative way a number of references was validated revealing that for our experiment a set of three references provides an appropriate normalization. Semi-quantitative PCR was prone to many handling errors and difficult to control while RT-qPCR was very sensitive to expression fluctuations of the reference genes