Suchergebnisse

This article shows that highly correlated measures can produce different results. We identify a democratization model from the literature and test it in more than 120 countries from 1951 to 1992. Then, we check whether the results are robust regarding measures of democracy, time periods, and levels of development. The findings show that measures do matter: Whereas some of the findings are robust, most of them are not. This explains, in part, why the debates on democracy have continued rather than been resolved. More important, it underscores the need for more careful use of measures and further testing to increase confidence in the findings. Scholars in comparative politics are drawn increasingly to large-N statistical analyses, often using data sets collected by others. As in any field, we show how they must be careful in choosing the most appropriate measures for their studies, without assuming that any correlated measure will do.

Meta‐analyses offer a rigorous and transparent systematic framework for synthesizing data that can be used for a wide range of research areas, study designs, and data types. Both the outcome of meta‐analyses and the meta‐analysis process itself can yield useful insights for answering scientific questions and making policy decisions. Development of the National Ambient Air Quality Standards illustrates many potential applications of meta‐analysis. These applications demonstrate the strengths and limitations of meta‐analysis, issues that arise in various data realms, how meta‐analysis design choices can influence interpretation of results, and how meta‐analysis can be used to address bias and heterogeneity. Reviewing available data from a meta‐analysis perspective can provide a useful framework and impetus for identifying and refining strategies for future research. Moreover, increased pervasiveness of a meta‐analysis mindset—focusing on how the pieces of the research puzzle fit together—would benefit scientific research and data syntheses regardless of whether or not a quantitative meta‐analysis is undertaken. While an individual meta‐analysis can only synthesize studies addressing the same research question, the results of separate meta‐analyses can be combined to address a question encompassing multiple data types. This observation applies to any scientific or policy area where information from a variety of disciplines must be considered to address a broader research question.

This paper suggests a three-stage procedure for the estimation of time-invariant and rarely changing variables in panel data models with unit effects. The first stage of the proposed estimator runs a fixed-effects model to obtain the unit effects, the second stage breaks down the unit effects into a part explained by the time-invariant and/or rarely changing variables and an error term, and the third stage reestimates the first stage by pooled OLS (with or without autocorrelation correction and with or without panel-corrected SEs) including the time-invariant variables plus the error term of stage 2, which then accounts for the unexplained part of the unit effects. We use Monte Carlo simulations to compare the finite sample properties of our estimator to the finite sample properties of competing estimators. In doing so, we demonstrate that our proposed technique provides the most reliable estimates under a wide variety of specifications common to real world data. Adapted from the source document.

Clustering is one of the most fundamental and essential data analysis techniques. Clustering can be used as an independent data mining task to discern intrinsic characteristics of data, or as a preprocessing step with the clustering results then used for classification, correlation analysis, or anomaly detection.Kogan and his co-editors have put together recent advances in clustering large and high-dimension data. Their volume addresses new topics and methods which are central to modern data analysis, with particular emphasis on linear algebra tools, opimization methods and statistical techniques. The contributions, written by leading researchers from both academia and industry, cover theoretical basics as well as application and evaluation of algorithms, and thus provide an excellent state-of-the-art overview.The level of detail, the breadth of coverage, and the comprehensive bibliography make this book a perfect fit for researchers and graduate students in data mining and in many other important related application areas.

Posthumous medical data donation (PMDD) for the purpose of legitimate, non-commercial and, potentially, very beneficial medical research has been sparsely discussed in legal scholarship to date. Conversely, quite an extensive social science and humanities research establishes benefits of this practice. It also finds that PMDD enables individuals to employ their altruistic motivations and aspirations by helping them participate in 'citizen's science' and medical research, thus supporting efforts in finding cures for some of the acutest diseases of today. There appears to be no jurisdiction where a regulatory framework supports and enables PMDD. This paper analyses whether and to what extent law and policy should enable this practice. We take a comparative approach, examining the position under both US and UK law, providing the first comparative legal account of this practice. We do not aim to suggest a detailed legal solution for PMDD, but rather key considerations and principles for legislative/policy reforms, which would support the practice of PMDD. We discuss organ donation and provide a comparative outlook with the aim of drawing lessons from this practice, and applying them to the regulation of PMDD. Our analysis is both normative and black letter since we consider arguments regarding the necessity of organ and data donation, as well as the law that regulates these practices.

This book provides a comprehensive discussion on urban growth and sprawl, and how they can be analyzed using remote sensing imageries. It compiles the views of numerous researchers that help in understanding a host of topics in urban growth and sprawl.