Biostatistics

This concise, easy-to-read pocket guide offers medical trainees, researchers, and clinicians at every level the perfect resource on Evidence Based Medicine (EBM). Based on the author's many years of experience teaching EBM to medical students and medical residents at Columbia University, this handy title addresses not only all the basic concepts and issues in EBM, but also takes an example-based approach and is replete with numerous illustrations. This brief book provides readers with all the tools needed to tell the good from the bad in healthcare research. It discusses every type of study design, from the assessment of diagnostic tests to clinical trials and meta-analysis. The work also introduces readers to novel methods, such as the Bayesian analysis of clinical trials. In addition, to help readers better retain the information, the guide includes thought-provoking review questions and answers in an appendix. In all, Pocket Evidence-Based Medicine: A Survival Guide for Clinicians and Students is an ideal resource for anyone who encounters statistics in their studies or career, including clinicians, researchers, trainees in medicine and graduate students in a wide range of other disciplines

Der SPIEGEL Bestseller Platz 1Fakten gegen Fakes!Die bekannte Wissenschaftsjournalistin Dr. Mai Thi Nguyen-Kim untersucht mit analytischem Scharfsinn und unbestechlicher Logik brennende Streitfragen unserer Gesellschaft. Mit Fakten und wissenschaftlichen Erkenntnissen kontert sie Halbwahrheiten, Fakes und Verschwörungsmythen - und zeigt, wo wir uns mangels Beweisen noch zurecht munter streiten dürfen.Themen:Die Legalisierung von Drogen, Videospiele, Gewalt, Gender Pay Gap, systemrelevante Berufe, Care-Arbeit, Lohngerechtigkeit, Big Pharma vs. Alternative Medizin, Homöopathie, klinische Studien, Impfpflicht, die Erblichkeit von Intelligenz, Gene vs. Umwelt, männliche und weibliche Gehirne, Tierversuche und von Corona bis Klimawandel: Wie politisch darf Wissenschaft sein?Fakten, wissenschaftlich fundiert und eindeutig belegt, sind Gold wert. Gerade dann, wenn in Gesellschaft und Politik über Reizthemen hitzig gestritten wird, braucht es einen Faktencheck, um die Dinge klarzustellen und Irrtümer und Fakes aus der Welt schaffen. Leider aber werden Fakten oft verkürzt, missverständlich präsentiert oder gerne auch mit subjektiver Meinung wild gemischt. Ein sachlicher Diskurs? Nicht mehr möglich. Dr. Mai Thi Nguyen-Kim räumt bei den derzeit beliebtesten Streitthemen mit diesem Missstand auf.Bestechend klarsichtig, wunderbar unaufgeregt und herrlich kurzweilig ermittelt sie anhand wissenschaftlicher Erkenntnisse das, was faktisch niemand in Abrede stellen kann, wenn es beispielsweise um Erblichkeit von Intelligenz, Gender Pay Gap, Klimawandel oder Legalisierung von Drogen geht. Mai Thi Nguyen-Kims Suche nach dem Kern der Wahrheit zeigt dabei nicht nur, was unanfechtbar ist und worauf wir uns alle einigen können. Mehr noch: Sie macht deutlich, wo die Fakten aufhören, wo Zahlen und wissenschaftliche Belege fehlen - wo wir also völlig berechtigt uns gegenseitig persönliche Meinungen an den Kopf werfen dürfen.Ein spannender und informativer Fakten- und Reality-Check, der beste Bullshit-Detektor für unsere angeblich postfaktische Zeit.

Markov State Models (MSM) sind der Goldstandard zur Modellierung biomolekularer Dynamik, da sie die Identifizierung und Analyse metastabiler Zustände ermöglichen. Die robuste Perron-Cluster-Cluster-Analyse (PCCA+) ist ein verbreiteter Spectral-Clustering-Algorithmus, der für das Clustering hochdimensionaler MSM verwendet wird. Da die PCCA+ auf reversible Prozesse beschränkt ist, wird sie zur Generalisierten PCCA+ (G-PCCA) verallgemeinert, die geeignet ist, nichtreversible Prozesse aufzuklären. Bernhard Reuter untersucht hier mittels G-PCCA die nichtthermischen Auswirkungen von Mikrowellen auf die Proteindynamik. Dazu führt er molekulardynamische Nichtgleichgewichtssimulationen des Amyloid-ß-(1-40)-Peptids durch und modelliert diese.¿Der Autor:Bernhard Reuter forscht in der Gruppe Methoden der Medizininformatik an der Eberhard-Karls-Universität Tübingen und der Gruppe Computational Molecular Design am Zuse Institut Berlin. Ein Schwerpunkt seiner Forschung ist die Simulation und Modellierung biomolekularer Nichtgleichgewichtssysteme. Er entwickelt u.a. datenbasierte Methoden zur Modellierung biomolekularer Nichtgleichgewichtsprozesse.

This book is a comprehensive and practical introduction of clinical epidemiology for students and practitioners. It covers both the basic principles and concepts of clinical epidemiology as well as its applications in various medical disciplines.It covers how to design, conduct, and interpret clinical studies using methods such as bias analysis, confounding control, causality assessment, diagnosis evaluation, prognosis prediction treatment comparison, and meta-analysis in this book. It also introduces how to apply these skills to real-world scenarios through case studies and examples that provide a fresh perspective on familiar topics. This book is a useful textbook for graduate and undergraduate students in medical schools, including MBBS (Bachelor of Medicine and Bachelor of Surgery) student.

Five years after Ronald Ross discovered the link between malaria and mosquitos, American entomologist Leland Howard wrote of the "mosquito evil" that occurs when "everybody's business is nobody's business." Howard's insight was largely ignored, but it captures what social scientists now refer to as the problem of collective action. When this problem persists in the context of malaria, individuals under-provide prevention and suffer from a higher prevalence of malaria. Imagine a group of people trying to drain a pond where mosquitoes breed. Everyone in the group faces an incentive to free ride, which can hinder their drainage efforts. Thus, when people fail to resolve issues related to collective action, they submit to the "mosquito evil" and, potentially, to malaria. This book explores Howard's logic, the economics of collective action, and the history, epidemiology, and public health of malaria to analyze the conditions under which peopleprivately resolve collective action problems associated with mosquito abatement and malaria prevention. Generally, people are more likely to resolve these problems when the benefits of abatement and prevention outweigh the costs. This logic is developed into a framework and applied to historical and modern-day issues related to malaria, including the lack or abundance of private prevention in the United States and in developing areas; malaria's resurgence in countries like China, Venezuela, and Bangladesh; and the difficulties of large-scale insecticide-treated bed net campaigns. Given this framework, we should develop a greater appreciation for entrepreneurial responses, civil society, market processes, and private forms of collective action.

The societal consequences of antimicrobial resistance (AMR) are severe. They include declining health outcomes from longer illnesses, prolonged stays in hospital, loss of protection for patients undergoing medical procedures, increased health care expenditure, and increased mortality. They also include declining global food security as AMR damages farm animal health and crop yields. Despite AMR being a transboundary crisis, concerted global initiatives that effectively combat AMR have been few and far between.Steering Against Superbugs analyses ways to reduce barriers and create opportunities for coordination. The expert contributions in this volume offer specific and original insights about what global governance of AMR means, and ways to help solve AMR issues. They show that effective governance relies crucially on pursuing local level implementation of key policies, and equitable recognition of solutions across multiple sectors within countries, and across the Global North and South. With the COVID-19 pandemic, societies across the world have been reminded of the devastating consequences of not being able to effectively counter global health threats. AMR is arguably one of the most severe long-term threats to human, animal, and environmental health. There is momentum for global political action around novel and emerging disease threats and Steering Against Superbugs contributes with original and insightful research to inform ongoing and future debates.

This is a comprehensive book series that comprises two distinct yet interconnected volumes. Volume I focuses on international relations and global politics, while Volume II delves into social sciences and humanities studies. Both volumes revolve around the central theme of the COVID-19 pandemic era, exploring its profound impact on various aspects of the world. In Volume I, scholars, and experts in the field of international relations delve into the intricate dynamics of global politics in the context of the pandemic. They analyse the shifting power dynamics, the role of international organisations, the challenges to global governance, and the geopolitical implications of the crisis. This book provides valuable insights into how the pandemic has shaped and transformed the international system, influencing state behaviour, diplomatic relations, and global cooperation. Volume II takes a multidisciplinary approach, examining the social, cultural, economic, and psychological dimensions ofthe COVID-19 pandemic. Experts from the fields of social sciences and humanities contribute their research and perspectives, offering critical analyses of the pandemic's effects on societies, communities, individuals, and various aspects of human life. Together, these two volumes provide a comprehensive exploration of the COVID-19 pandemic's impact on world politics, society, and human experiences. By bringing together scholars from different disciplines, the book series offers a holistic understanding of the challenges and opportunities presented by this unprecedented global crisis. It serves as a valuable resource for academics, policymakers, and anyone seeking to comprehend and navigate the complexities of the COVID-19 era.

This book provides a comprehensive review of novel adaptive trial designs for targeted therapies and immunotherapies. This book covers a wide range of novel statistical designs for various clinical settings, including early phase dose-escalation study, proof-of-concept trials, and confirmatory studies with registrational. The book includes real-life examples and software to facilitate practitioners to learn and use the designs in practice.

This book addresses the many ethical issues and extraordinary risks that nurses and others are facing during the COVID-19 pandemic, which creates physical, emotional, and economic burdens, affecting nurses' overall health and well-being. Nurses are essential front-line clinicians across all health care settings and in every nation. The COVID-19 pandemic caused by the novel SARs-CoV-2 virus has affected children, adults, and communities within and across all societies. Nurses, too, have contracted the virus and died from the disease. They have also seen their colleagues, family members, and friends hospitalized or in intensive care units struggling to survive. Nursing's professionalism and disciplinary resolve to care for patients and families amidst confusion, misinformation, and shifting guidelines has been called "heroic" by the public. How much risk should nurses be expected to accept during a pandemic? How do nurses help patients and families find comfort and dignity at the end-of-life? How do we help nurses who are suffering from moral distress and mental health concerns from what they have seen, been asked to do, or are unable to provide? And, how does society move forward from a pandemic that has challenged our basic ethical principles of justice and what is "fair, good and right" in caring for those who need care, including the most vulnerable and nurses themselves? This book addresses these and other ethical concerns that nurses are facing in their day-to-day clinical practice; experiences shared with patients, families, and colleagues. Although this book was written while the pandemic was still raging across the United States and globally, the events needed to be told as they were unfolding. This book helps us to learn from both the successes and failures that are affecting so many across the globe, including those on whom the public relies on to provide quality, compassionate, and expert care when they are sick: nurses.

This book provides an overview of the emerging topics in biostatistical theories and methods through their applications to evidence-based global health research and decision-making. It brings together some of the top scholars engaged in biostatistical method development on global health to highlight and describe recent advances in evidence-based global health applications. The volume is composed of five main parts: data harmonization and analysis; systematic review and statistical meta-analysis; spatial-temporal modeling and disease mapping; Bayesian statistical modeling; and statistical methods for longitudinal data or survival data. It is designed to be illuminating and valuable to both expert biostatisticians and to health researchers engaged in methodological applications in evidence-based global health research. It is particularly relevant to countries where global health research is being rigorously conducted.

This book offers an accessible introduction to random walk and diffusion models at a level consistent with the typical background of students in the life sciences. In recent decades these models have become widely used in areas far beyond their traditional origins in physics, for example, in studies of animal behavior, ecology, sociology, sports science, population genetics, public health applications, and human decision making. Developing the main formal concepts, the book provides detailed and intuitive step-by-step explanations, and moves smoothly from simple to more complex models. Finally, in the last chapter, some successful and original applications of random walk and diffusion models in the life and behavioral sciences are illustrated in detail. The treatment of basic techniques and models is consolidated and extended throughout by a set of carefully chosen exercises.

This textbook provides a step-by-step introduction to the tools and principles of high-dimensional statistics. Each chapter is complemented by numerous exercises, many of them with detailed solutions, and computer labs in R that convey valuable practical insights. The book covers the theory and practice of high-dimensional linear regression, graphical models, and inference, ensuring readers have a smooth start in the field. It also offers suggestions for further reading. Given its scope, the textbook is intended for beginning graduate and advanced undergraduate students in statistics, biostatistics, and bioinformatics, though it will be equally useful to a broader audience.

Machine learning and big data is hot. It is, however, virtually unused in clinical trials. This is so, because randomization is applied to even out multiple variablesModern medical computer files often involve hundreds of variables like genes and other laboratory values, and computationally intensive methods are requiredThis is the first publication of clinical trials that have been systematically analyzed with machine learning. In addition, all of the machine learning analyses were tested against traditional analyses. Step by step statistics for self-assessments are includedThe authors conclude, that machine learning is often more informative, and provides better sensitivities of testing than traditional analytic methods do

Presents research from the premier conference on statistical research and applications in pharmaceutical R&DOffers original, peer-reviewed researchAddresses biosimilarity, bioequivalence, clinical trial design, and subgroup identification - emergent topics critical to current pharmaceutical R&DIncludes novel topics for statistical methodology research

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Mathematical and Statistical Estimation Approaches in Epidemiology compiles t- oretical and practical contributions of experts in the analysis of infectious disease epidemics in a single volume. Recent collections have focused in the analyses and simulation of deterministic and stochastic models whose aim is to identify and rank epidemiological and social mechanisms responsible for disease transmission. The contributions in this volume focus on the connections between models and disease data with emphasis on the application of mathematical and statistical approaches that quantify model and data uncertainty. The book is aimed at public health experts, applied mathematicians and sci- tists in the life and social sciences, particularly graduate or advanced undergraduate students, who are interested not only in building and connecting models to data but also in applying and developing methods that quantify uncertainty in the context of infectious diseases. Chowell and Brauer open this volume with an overview of the classical disease transmission models of Kermack-McKendrick including extensions that account for increased levels of epidemiological heterogeneity. Their theoretical tour is followed by the introduction of a simple methodology for the estimation of, the basic reproduction number,R . The use of this methodology 0 is illustrated, using regional data for 1918-1919 and 1968 in uenza pandemics.

1 Beobachtungsdaten.- 1.1 Skalentypen.- 1.2 Elementare Rechenoperationen.- 1.3 Matrizen.- 1.4 Gleichungssysteme.- 1.5 Aufgaben.- 2 Funktionen.- 2.1 Von der Beobachtung zur Funktion.- 2.2 Lineare Funktionen.- 2.3 Spezielle rationale Funktionen.- 2.4 Exponential- und Logarithmusfunktionen.- 2.5 Sinusförmige Veränderungen.- 2.6 Aufgaben.- 3 Differenzengleichungen.- 3.1 Modellbildung auf diskreten Zeitskalen.- 3.2 Lösung von Differenzengleichungen.- 3.3 Konvergente und divergente Folgen.- 3.4 Qualitative Untersuchung von Differenzengleichungen.- 3.5 Aufgaben.- 4 Differentiation und Integration.- 4.1 Der Differentialquotient.- 4.2 Beschreibung von Funktionen mit Hilfe der Ableitung.- 4.3 Bestimmtes und unbestimmtes Integral.- 4.4 Aufgaben.- 5 Differentialgleichungen.- 5.1 Modellbildung mit Differentialgleichungen.- 5.2 Differentialgleichungen erster Ordnung.- 5.3 Differentialgleichungen zweiter Ordnung.- 5.4 Differentialgleichungssysteme.- 5.5 Aufgaben.- Anhang: Lösungen der Aufgaben.- Literatur.

Dieses Buch ist als EinfUhrung in die Theoretische Okologie gedacht. Den Begriff "okologisches Modell" habe ich im Titel absichtlich vermieden, denn hierzu ziihlen ganz verschiedene Methoden der mathematischen Beschreibung von okologischen V orgiingen. Ziel einer Theorie ist es, ein Verstandnis fUr die Vor­ gange und funktionellen Zusammenhange eines Fachgebietes zu erlangen. Dies kann natiirlich auch ohne Mathematik durch Denken in verbalen Kategorien ge­ schehen. Jeder Naturwissenschaftler ist angehalten, iiber das, was er im Experi­ ment oder in der freien Natur gefunden hat, nachzudenken. Dies sind bereits die ersten Ansiitze zu einer Theorie. Eine mathematische Theorie ist nun' nichts weiter, als eine Fortsetzung dieses Denkens in einer anderen Spnlche - der Sprache der Mathematik. Dabei muB immer das okologische Problem im Vorder­ grund stehen. Die Mathematik ist nur ein" mogliches Hilfsmittel, urn em besseres Verstandnis fUr die okologischen Vorgange zu bekommen. Anders als in der Theoretischen Physik sind in der Okologie kaum all­ gemeingiiltige Prinzipien und Gesetze gefunden worden, aus denen man die Losung eines speziellen Problems deduzieren kann. Eine Ursache hierfUr mag neben der Komplexitat von Okosystemen auch die Schwierigkeit sein, Modelle und Theorien der Okologie durch gezielte Experimente in der freien Natur zu iiberpriifen. Das Fehlen einer allgemein anerkannten Theorie hat zur Folge, daB die Auswahl der induktiv aufgestellten Modelle subjektiv sein muB. So wird man­ cher Leser einzelnen Darstellungen dieses Buches nicht zustimmen. Es gibt recht verschiedene Methoden des Modellierens. Mitunter ist nicht einmal klar, mit welcher Fragestellung man an die Objekte herangehen solI.

Der vorliegende Text wurde für Studierende biowissenschaftlicher Fächer in den Anfangssemestern konzipiert, eignet sich aber auch für Schüler in Biologie- und Chemie-Leistungskursen. Er soll Leser ohne detaillierte Vorkenntnisse in die Physikalische Chemie einführen und auf die Lektüre umfangreicherer und schwierigerer Lehrbücher und wissenschaftlicher Veröffentlichungen auf diesem Gebiet vorbereiten. Die Darstellung konzentriert sich auf die Bereiche der Physikalischen Chemie, die für Biowissenschaftler von besonderem Interesse sind (Gase, Lösungen, chemisches Gleichgewicht, Thermodynamik, allgemeine Reaktionskinetik, Enzymkinetik, Elektrochemie und Membrantransport). Dabei wird besonderer Wert auf eine sorgfältige Herleitung und Erklärung wichtiger quantitativer Beziehungen gelegt. Zahlreiche numerische Beispiele verdeutlichen die Verwendung der physikalisch-chemischen Gleichungen. Der Anhang enthält u.a. eine kurze Erläuterung der mathematischen Zusammenhänge, die ein tieferes Verständnis der wichtigsten Teilbereiche fördern können.

Keine ausführliche Beschreibung für "Therapeutische Probleme, Epidemiologie, Toxikologie, Nutzen-Risiko-Abwägung" verfügbar.