Discover best practices for real world data research with SAS code and examples Real world health care data is common and growing in use with sources such as observational studies, patient registries, electronic medical record databases, insurance healthcare claims databases, as well as data from pragmatic trials. This data serves as the basis for the growing use of real world evidence in medical decision-making. However, the data itself is not evidence. Analytical methods must be used to turn real world data into valid and meaningful evidence. Real World Health Care Data Analysis: Causal Methods and Implementation Using SAS brings together best practices for causal comparative effectiveness analyses based on real world data in a single location and provides SAS code and examples to make the analyses relatively easy and efficient. The book focuses on analytic methods adjusted for time-independent confounding, which are useful when comparing the effect of different potential interventions on some outcome of interest when there is no randomization. These methods include: propensity score matching, stratification methods, weighting methods, regression methods, and approaches that combine and average across these methods methods for comparing two interventions as well as comparisons between three or more interventions algorithms for personalized medicine sensitivity analyses for unmeasured confounding
This book guides researchers in performing and presenting high-quality analyses of all kinds of non-randomized studies, including analyses of observational studies, claims database analyses, assessment of registry data, survey data, pharmaco-economic data, and many more applications. The text is sufficiently detailed to provide not only general guidance, but to help the researcher through all of the standard issues that arise in such analyses. Just enough theory is included to allow the reader to understand the pros and cons of alternative approaches and when to use each method. The numerous contributors to this book illustrate, via real-world numerical examples and SAS code, appropriate implementations of alternative methods. The end result is that researchers will learn how to present high-quality and transparent analyses that will lead to fair and objective decisions from observational data.
Discover best practices for real world data research with SAS code and examples Real world health care data is common and growing in use with sources such as observational studies, patient registries, electronic medical record databases, insurance healthcare claims databases, as well as data from pragmatic trials. This data serves as the basis for the growing use of real world evidence in medical decision-making. However, the data itself is not evidence. Analytical methods must be used to turn real world data into valid and meaningful evidence. Real World Health Care Data Analysis: Causal Methods and Implementation Using SAS brings together best practices for causal comparative effectiveness analyses based on real world data in a single location and provides SAS code and examples to make the analyses relatively easy and efficient. The book focuses on analytic methods adjusted for time-independent confounding, which are useful when comparing the effect of different potential interventions on some outcome of interest when there is no randomization. These methods include: propensity score matching, stratification methods, weighting methods, regression methods, and approaches that combine and average across these methods methods for comparing two interventions as well as comparisons between three or more interventions algorithms for personalized medicine sensitivity analyses for unmeasured confounding
What have been the general ideas about the growth of Barcelona over the last fifty years? Why were they so controversial? Why is the Metro still the Cinderella of the Metropolitan system? Who extended the Cerdà plan to the River Besòs? The answer to these questions and many more can be found in this book which explains a century of urbanism in Barcelona, stressing two key periods: the years in which Barcelona was conceived as a capital city and the years in which it was converted into a metropolis. The book closes by raising current topics that have dominated discussion about the city from the turn of the 20th Century and which are crucial to its future. The architect and university lecturer Josep Parcerisa offers us the keys to understanding the city and its recent history. Throughout the book, the reader will find more 300 images that often speak for themselves. For the first time, the urbanism of the city is explained and can be visualised at the same time.
This monograph presents some theoretical and computational aspects of the parameterization method for invariant manifolds, focusing on the following contexts: invariant manifolds associated with fixed points, invariant tori in quasi-periodically forced systems, invariant tori in Hamiltonian systems and normally hyperbolic invariant manifolds. This book provides algorithms of computation and some practical details of their implementation. The methodology is illustrated with 12 detailed examples, many of them well known in the literature of numerical computation in dynamical systems. A public version of the software used for some of the examples is available online. The book is aimed at mathematicians, scientists and engineers interested in the theory and applications of computational dynamical systems.
The role of institutions is to establish the domains of public activity and the rules to select leaders. Democratic regimes organize in simple institutional frameworks to foster the concentration of power and alternative successive absolute winners and losers. They favour political satisfaction of relatively small groups, as well as policy instability. In contrast, pluralistic institutions produce multiple winners, including multiparty co-operation and agreements. They favour stable, moderate, and consensual policies that can satisfy large groups' interests on a great number of issues. The more complex the political institutions, the more stable and socially efficient the outcome will be. This book develops an extensive analysis of this relationship. It explores concepts, questions and insights based on social choice theory, while empirical focus is cast on more than 40 democratic countries and a few international organizations from late medieval times to the present. The book argues that pluralistic democratic institutions are judged to be better than simple formula of their higher capacity of producing socially satisfactory results.
This volume contains a selection of three translations of articles by Josep M. Pujol (Barcelona, 1947–2012), one in each of the three areas that he defined to characterise his work in the field of folklore: the theory of interactive artistic communication; the history of folklore studies and folk literature; and folk narrative. The three articles give a taste of the important contributions he made to the study of folklore, and which have been studied and contextualised by Carme Oriol in the introduction that precedes the three texts. This edition also includes the complete folkloric bibliography of Josep M. Pujol in chronological order, with all the references.
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