1,014 research outputs found

    Sufficient Covariate, Propensity Variable and Doubly Robust Estimation

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    Statistical causal inference from observational studies often requires adjustment for a possibly multi-dimensional variable, where dimension reduction is crucial. The propensity score, first introduced by Rosenbaum and Rubin, is a popular approach to such reduction. We address causal inference within Dawid's decision-theoretic framework, where it is essential to pay attention to sufficient covariates and their properties. We examine the role of a propensity variable in a normal linear model. We investigate both population-based and sample-based linear regressions, with adjustments for a multivariate covariate and for a propensity variable. In addition, we study the augmented inverse probability weighted estimator, involving a combination of a response model and a propensity model. In a linear regression with homoscedasticity, a propensity variable is proved to provide the same estimated causal effect as multivariate adjustment. An estimated propensity variable may, but need not, yield better precision than the true propensity variable. The augmented inverse probability weighted estimator is doubly robust and can improve precision if the propensity model is correctly specified

    Experimental and Numerical Comparison of Flexural Capacity of Light Gage Cold Formed Steel Roof Deck

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    This paper presents an analysis of experimental data and compares it to two numerical analysis methods of light gage cold formed steel roof deck. The flexural capacity was determined upon the first failure mode of the light gage cold formed steel roof deck. A comparison of the experimental data was made to both the effective width method and the direct strength method. The objective of the comparison was to have a physical test provide the actual behavior of the light gage cold formed steel roof deck and grade how well the numerical analysis, effective width and direct strength methods, compare against the results. Material testing samples were taken from the steel roof deck and evaluated for the actual yield stress. This allowed for the most accurate comparison between the experimental results with the numerical analysis since the exact yield strength was used in calculation. It was found that the effective width method and the direct strength method vary in their prediction of the nominal moment capacity across material grades and deck thickness but tend to converge to a constant ratio, MnDSM /Mn EWM, at thicker deck gages. The effective width method was found to be more accurate for thinner gage steel roof deck, while the direct strength method was found to be more accurate for thicker gage steel roof deck. The effective width method is better at predicting the strength of steel roof deck, particularly the thinner gage ones, while the direct strength method provided a much quicker process to find the flexural capacity of the deck. Both methods can be used to determine the capacity of the deck and it is up to the end user to determine which method is appropriate for the given application

    Computational algebraic methods in efficient estimation

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    A strong link between information geometry and algebraic statistics is made by investigating statistical manifolds which are algebraic varieties. In particular it it shown how first and second order efficient estimators can be constructed, such as bias corrected Maximum Likelihood and more general estimators, and for which the estimating equations are purely algebraic. In addition it is shown how Gr\"obner basis technology, which is at the heart of algebraic statistics, can be used to reduce the degrees of the terms in the estimating equations. This points the way to the feasible use, to find the estimators, of special methods for solving polynomial equations, such as homotopy continuation methods. Simple examples are given showing both equations and computations. *** The proof of Theorem 2 was corrected by the latest version. Some minor errors were also corrected.Comment: 21 pages, 5 figure

    The Eurace@Unibi Model: An Agent-Based Macroeconomic Model for Economic Policy Analysis

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    Dawid H, Gemkow S, Harting P, van der Hoog S, Neugart M. The Eurace@Unibi Model: An Agent-Based Macroeconomic Model for Economic Policy Analysis. Working Papers in Economics and Management. Vol 05-2012. Bielefeld: Bielefeld University, Department of Business Administration and Economics; 2012.This document provides a description of the modeling assumptions and economic features of the Eurace@Unibi model. Furthermore, the document shows typical patterns of the output generated by this model and compares it to empirically observable stylized facts. The Eurace@Unibi model provides a representation of a closed macroeconomic model with spatial structure. The main objective is to provide a micro-founded macroeconomic model that can be used as a unified framework for policy analysis in different economic policy areas and for the examination of generic macroeconomic research questions. In spite of this general agenda the model has been constructed with certain specific research questions in mind and therefore certain parts of the model, e.g. the mechanisms driving technological change, have been worked out in more detail than others. The purpose of this document is to give an overview over the model itself and its features rather than discussing how insights into particular economic issues can be obtained using the Eurace@Unibi model. The model has been designed as a framework for economic analysis in various domains of economics. A number of economic issues have been examined using (prior versions of) the model (see Dawid et al. (2008), Dawid et al. (2009), Dawid et al. (2011a), Dawid and Harting (2011), van der Hoog and Deissenberg (2011), Cincotti et al. (2010)) and recent extensions of the model have substantially extended its applicability in various economic policy domains, however results of such policy analyses will be reported elsewhere. Whereas the overall modeling approach, the different modeling choices and the economic rationale behind these choices is discussed in some detail in this document, no detailed description of the implementation is given. Such a detailed documentation is provided in the accompanying document Dawid et al. (2011b)

    Spatial interactions in agent-based modeling

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    Agent Based Modeling (ABM) has become a widespread approach to model complex interactions. In this chapter after briefly summarizing some features of ABM the different approaches in modeling spatial interactions are discussed. It is stressed that agents can interact either indirectly through a shared environment and/or directly with each other. In such an approach, higher-order variables such as commodity prices, population dynamics or even institutions, are not exogenously specified but instead are seen as the results of interactions. It is highlighted in the chapter that the understanding of patterns emerging from such spatial interaction between agents is a key problem as much as their description through analytical or simulation means. The chapter reviews different approaches for modeling agents' behavior, taking into account either explicit spatial (lattice based) structures or networks. Some emphasis is placed on recent ABM as applied to the description of the dynamics of the geographical distribution of economic activities, - out of equilibrium. The Eurace@Unibi Model, an agent-based macroeconomic model with spatial structure, is used to illustrate the potential of such an approach for spatial policy analysis.Comment: 26 pages, 5 figures, 105 references; a chapter prepared for the book "Complexity and Geographical Economics - Topics and Tools", P. Commendatore, S.S. Kayam and I. Kubin, Eds. (Springer, in press, 2014

    Effects of Epistasis and Pleiotropy on Fitness Landscapes

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    The factors that influence genetic architecture shape the structure of the fitness landscape, and therefore play a large role in the evolutionary dynamics. Here the NK model is used to investigate how epistasis and pleiotropy -- key components of genetic architecture -- affect the structure of the fitness landscape, and how they affect the ability of evolving populations to adapt despite the difficulty of crossing valleys present in rugged landscapes. Populations are seen to make use of epistatic interactions and pleiotropy to attain higher fitness, and are not inhibited by the fact that valleys have to be crossed to reach peaks of higher fitness.Comment: 10 pages, 6 figures. To appear in "Origin of Life and Evolutionary Mechanisms" (P. Pontarotti, ed.). Evolutionary Biology: 16th Meeting 2012, Springer-Verla

    Using Crowdsourcing for Fine-Grained Entity Type Completion in Knowledge Bases

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    Recent years have witnessed the proliferation of large-scale Knowledge Bases (KBs). However, many entities in KBs have incomplete type information, and some are totally untyped. Even worse, fine-grained types (e.g., BasketballPlayer) containing rich semantic meanings are more likely to be incomplete, as they are more difficult to be obtained. Existing machine-based algorithms use predicates (e.g., birthPlace) of entities to infer their missing types, and they have limitations that the predicates may be insufficient to infer fine-grained types. In this paper, we utilize crowdsourcing to solve the problem, and address the challenge of controlling crowdsourcing cost. To this end, we propose a hybrid machine-crowdsourcing approach for fine-grained entity type completion. It firstly determines the types of some ‚Äúrepresentative‚ÄĚ entities via crowdsourcing and then infers the types for remaining entities based on the crowdsourcing results. To support this approach, we first propose an embedding-based influence for type inference which considers not only the distance between entity embeddings but also the distances between entity and type embeddings. Second, we propose a new difficulty model for entity selection which can better capture the uncertainty of the machine algorithm when identifying the entity types. We demonstrate the effectiveness of our approach through experiments on real crowdsourcing platforms. The results show that our method outperforms the state-of-the-art algorithms by improving the effectiveness of fine-grained type completion at affordable crowdsourcing cost.Peer reviewe

    The blp locus of Streptococcus pneumoniae plays a limited role in the selection of which strains can co-colonize the human nasopharynx.

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    Nasopharyngeal colonization is important for Streptococcus pneumoniae evolution, providing the opportunity for horizontal gene transfer when multiple strains co-occur. Although colonization with more than one strain of pneumococcus is common, the factors that influence the ability of strains to co-exist are not known. A highly variable blp (bacteriocin-like peptide) locus has been identified in all sequenced strains of S. pneumoniae This locus controls the regulation and secretion of bacteriocins, small peptides that target other bacteria. In this study, we analyzed a series of co-colonizing isolates to evaluate the impact of the blp locus on human colonization to determine whether competitive phenotypes of bacteriocin secretion restrict co-colonization.We identified a collection of 135 nasopharyngeal samples with two or more strains totaling 285 isolates. The blp locus of all strains was characterized genetically with regards to pheromone type, bacteriocin/immunity content and potential for locus functionality. Inhibitory phenotypes of bacteriocin secretion and locus activity were assessed through overlay assays. Isolates from single colonization (n=298) were characterized for comparison.Co-colonizing strains had a high diversity of blp cassettes; approximately one third displayed an inhibitory phenotype in vitro Despite in vitro evidence of competition, pneumococci co-colonized individuals independently of their blp pheromone type (p=0.577), bacteriocin/immunity content, blp locus activity (p=0.798) and inhibitory phenotype (p=0.716). In addition, no significant differences were observed when single and co-colonizing strains were compared.Despite clear evidence of blp-mediated competition in experimental models, our study suggests that the blp locus plays a limited role in restricting pneumococcal co-colonization in humans. IMPORTANCE: Nasopharyngeal colonization with Streptococcus pneumoniae (pneumococcus) is important for pneumococcal evolution as it represents the major site for horizontal gene transfer when multiple strains co-occur, a phenomenon known as co-colonization. Understanding how pneumococcal strains interact within the competitive environment of the nasopharynx is of chief importance in the context of pneumococcal ecology. In this study we used an unbiased collection of naturally co-occurring pneumococcal strains and showed that a biological process frequently used by bacteria for competition - bacteriocin production - is not decisive in the co-existence of pneumococci in the host, contrary to what has been shown in experimental models
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