• Thorough discussion of both BNP and its interplay with causal inference and missing data • How to use BNP and g-computation for causal inference and nonignorable missingness • How to derive and calibrate sensitivity parameters to assess sensitivity to deviations from uncheckable causal and/or missingness assumptions • Detailed case studies illustrating the application of BNP methods to causal inference and missing data • R-code and/or packages to implement BNP in causal inference and missing data problems

Several fundamental advances were announced at the Seventh International Symposium on Molecular Plant--Microbe Interactions held in Edinburgh in 1994. These included the cloning and identification of plant resistance genes involved in recognition of pathogens; the description of genetically engineered plants with novel resistance to pathogens; characterization of the molecular basis of pathogenicity of fungal and bacterial plant pathogens; and the mechanisms of communication used during recognition between symbiotic rhizobia and their host legumes. Participants in the Symposium contributed a series of papers that represent the leading edge of research in this important area of plant and microbial science. These articles are brought together to form this book, which will be essential reading for research workers, advanced students and others interested in keeping abreast of this rapidly developing area.

Drawing from the authors' own work and from the most recent developments in the field, Missing Data in Longitudinal Studies: Strategies for Bayesian Modeling and Sensitivity Analysis describes a comprehensive Bayesian approach for drawing inference from incomplete data in longitudinal studies. To illustrate these methods, the authors employ several data sets throughout that cover a range of study designs, variable types, and missing data issues. The book first reviews modern approaches to formulate and interpret regression models for longitudinal data. It then discusses key ideas in Bayesian inference, including specifying prior distributions, computing posterior distribution, and assessing model fit. The book carefully describes the assumptions needed to make inferences about a full-data distribution from incompletely observed data. For settings with ignorable dropout, it emphasizes the importance of covariance models for inference about the mean while for nonignorable dropout, the book studies a variety of models in detail. It concludes with three case studies that highlight important features of the Bayesian approach for handling nonignorable missingness. With suggestions for further reading at the end of most chapters as well as many applications to the health sciences, this resource offers a unified Bayesian approach to handle missing data in longitudinal studies.

Several fundamental advances were announced at the Seventh International Symposium on Molecular Plant--Microbe Interactions held in Edinburgh in 1994. These included the cloning and identification of plant resistance genes involved in recognition of pathogens; the description of genetically engineered plants with novel resistance to pathogens; characterization of the molecular basis of pathogenicity of fungal and bacterial plant pathogens; and the mechanisms of communication used during recognition between symbiotic rhizobia and their host legumes. Participants in the Symposium contributed a series of papers that represent the leading edge of research in this important area of plant and microbial science. These articles are brought together to form this book, which will be essential reading for research workers, advanced students and others interested in keeping abreast of this rapidly developing area.

On 11 March 1943, the Chief of the British Imperial General Staff, Field Marshal Sir Alan Brooke, made a momentous decision in committing an entire British armored division, the 79th, to the task of developing equipment, tactics, and capabilities to penetrate the "Atlantic Wall" in anticipation of an Allied amphibious invasion of northwest Europe. British leaders chose Major-General Sir Percy Hobart to command this division, largely because of Hobart's affinity for leading and training armored formations, but also due to Hobart's reputation as an individualist, known to seek out unique solutions to unforeseen challenges. This thesis examines the wartime history of this unit--concentrating on aspects of equipment, tactics, organization and leadership that enabled it to ultimately succeed beyond anyone's expectations. More important, this organization provides valuable lessons for current transformation efforts. The key lessons that this subject provide include: the need for leadership that combines vision with action; a close cooperation between the military-industrial complex and the end user; and allowing space in the force structure for a unit that can perform not only standard combat missions, but can also serve as experimentation test-bed and conduit for new ideas, whether in the form of capabilities, organizational structure, or doctrine.