25. Multiple Imputation for Nonresponse in Surveys. By D. B. Rubin. ISBN 0 471 08705 X. Wiley, Chichester, 1987. 258 pp. £30.25.

Multiple Imputation for Nonresponse in Surveys

Economics and Information Theory

A tool changer is disclosed for automatically removing a working tool after having been used from the spindle of a machine tool such as a vertical milling machine, transferring the used working tool to a rack which stores a plurality of working tools, picking up from the rack another working tool for the next machining operation, transferring such new working tool to the spindle, and operatively mounting such new working tool on the spindle.

Temperature and Organism Size—A Biological Law for Ectotherms?

Beneficial microbes in the microbiome of plant roots improve plant health. Induced systemic resistance (ISR) emerged as an important mechanism by which selected plant growth–promoting bacteria and fungi in the rhizosphere prime the whole plant body for enhanced defense against a broad range of pathogens and insect herbivores. A wide variety of root-associated mutualists, including Pseudomonas, Bacillus, Trichoderma, and mycorrhiza species sensitize the plant immune system for enhanced defense without directly activating costly defenses. This review focuses on molecular processes at the interface between plant roots and ISR-eliciting mutualists, and on the progress in our understanding of ISR signaling and systemic defense priming. The central role of the root-specific transcription factor MYB72 in the onset of ISR and the role of phytohormones and defense regulatory proteins in the expression of ISR in aboveground plant parts are highlighted. Finally, the ecological function of ISR-inducing microbes in the root microbiome is discussed.

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Induced systemic resistance by beneficial microbes

The statistical literature on tests to compare treatments after the analysis of variance is reviewed, and the use of these tests in ecology is examined. Monte Carlo simulations on normal and lognormal data indicate that many of the tests commonly used are inappropriate or inefficient. Particular tests are recommended for unplanned multiple comparisons on the basis of controlling experimentwise type I error rate and providing maximum power. These include tests for parametric and nonparametric cases, equal and unequal sample sizes, homogeneous and heterogeneous variances, non-independent means (repeated measures or adjusted means), and comparing treatments to a control. Formulae and a worked example are provided. The problem of violations of assumptions, especially variance heterogeneity, was investigated using simulations, and particular strategies are recommended. The advantages and use of planned comparisons in ecology are discussed, and the philosophy of hypothesis testing with unplanned multiple comparisons is consid- ered in relation to confidence intervals and statistical estimation.

https://www.fc.up.pt/pessoas/amsantos/support/dayquin1989.pdf

Comparisons of Treatments After an Analysis of Variance in Ecology

Epidemics and Plant Disease Epidemiology Monitoring Epidemics: Host Monitoring Epidemics: Environment Monitoring Epidemics: Pathogen Monitoring Epidemics: Disease Modeling and Data Analysis Temporal Analysis of Epidemics I Temporal Analysis of Epidemics Spatial Aspects of Plant Disease Epidemics I: Dispersal Gradients of Long Range Transport Spatial Aspects of Plant Disease Epidemics II: Analysis of Spatial Pattern Simulation Models of Plant Disease Designing Experiments and Sampling Crop Loss Assessment and Modelling Forecasting Plant Diseases.

Introduction to Plant Disease Epidemiology

Study of plant disease epidemics

The study of plant disease epidemics

Plant disease severity often is assessed using an ordinal rating scale rather than a continuous scale of measurement. Although such data usually should be analyzed with nonparametric methods, and not with the typical parametric techniques (such as analysis of variance), limitations in the statistical methodology available had meant that experimental designs generally could not be more complicated than a one-way layout. Very recent advancements in the theoretical formulation of hypotheses and associated test statistics within a nonparametric framework, together with development of software for implementing the methods, have made it possible for plant pathologists to analyze properly ordinal data from more complicated designs using nonparametric techniques. In this paper, we illustrate the nonparametric analysis of ordinal data obtained from two-way factorial designs, including a repeated measures design, and show how to quantify the effects of experimental factors on ratings through estimated rela...

https://apsjournals.apsnet.org/doi/pdfplus/10.1094/PHYTO.2004.94.1.33

Nonparametric analysis of ordinal data in designed factorial experiments.

The statistical properties of disease incidence are reviewed and used to characterize spatial patterns of diseased entities (e.g. plants), satisfy assumptions of statistical analyses, and quantify change in incidence over time. Frequency of diseased plants can be represented by the binomial or, more commonly, the beta-binomial distribution. Spatial patterns of disease can be described by the aggregation parameter of the beta-binomial distribution, index of dispersion and related statistics, parameters of the binary form of the power law, as well as measures of spatial autocorrelation between sampling units. Disease incidence over time can be represented by continuous- and discrete-time nonlinear disease progress models, such as the logistic, and by autoregressive, integrated, moving average models. Ultimately, simultaneous spatio-temporal analyses can be performed to understand the dynamics of disease incidence in populations.

Laurence V. Madden

Papers

Introduction to Plant Disease Epidemiology

Study of plant disease epidemics

The study of plant disease epidemics

Nonparametric analysis of ordinal data in designed factorial experiments.

Plant disease incidence: distributions, heterogeneity, and temporal analysis