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Книги з теми "Design of observational studies"

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Автор: Grafiati

Опубліковано: 10 грудня 2022

Оновлено: 28 січня 2023

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1

Rosenbaum, Paul R. Design of Observational Studies. New York, NY: Springer New York, 2010. http://dx.doi.org/10.1007/978-1-4419-1213-8.

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2

Rosenbaum, Paul R. Design of Observational Studies. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-46405-9.

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3

Rosenbaum, Paul R. Observational studies. New York: Springer-Verlag, 1995.

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4

Observational studies. 2nd ed. New York: Springer, 2002.

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5

Rosenbaum, Paul R. Observational Studies. New York, NY: Springer New York, 1995. http://dx.doi.org/10.1007/978-1-4757-2443-1.

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6

Rosenbaum, Paul R. Observational Studies. New York, NY: Springer New York, 2002. http://dx.doi.org/10.1007/978-1-4757-3692-2.

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7

J, Bodilly Susan, Rand Institute on Education & Training., and New American Schools Development Corporation., eds. Designing new American schools: Baseline observations on nine design teams. Santa Monica, CA: Rand, 1995.

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8

Thrusfield, Michael. Introduction to veterinary observational studies. Roslin: Society for Veterinary Epidemiology and Preventive Medicine, 1985.

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9

Thrusfield, M. V. An introduction to veterinary observational studies. [Edinburgh]: Society for Veterinary Epidemiology and Preventive Medicine, 1985.

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10

Nauta, Jozef. Statistics in Clinical and Observational Vaccine Studies. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-37693-2.

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11

Hughes, Alain E. Scientific and ethical approaches for observational exposure studies. Edited by National Exposure Research Laboratory (U.S.). New York: Nova Science Pub., Inc., 2010.

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12

Hackshaw, Allan. A Concise Guide to Observational Studies in Healthcare. Chichester, UK: John Wiley & Sons, Ltd, 2014. http://dx.doi.org/10.1002/9781118527122.

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13

Kimura, Mariko. Observational and Theoretical Studies on Dwarf-nova Outbursts. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-8912-6.

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14

Grazia, Valsecchi Maria, ed. Analysing survival data from clinical trials and observational studies. Chichester: J. Wiley, 1995.

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15

Wada, Yuuki. Observational Studies of Photonuclear Reactions Triggered by Lightning Discharges. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-0459-1.

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16

Alberta. Alberta Education. Career and Technology Studies Program. Design studies. Edmonton, Alta: Alberta Education, Career and Technology Studies, 1992.

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17

Fedde, Kalverboer Alex, and Alberts Ed, eds. Developmental biopsychology: Experimental and observational studies in children at risk. Ann Arbor: University of Michigan Press, 1990.

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18

Schubert, Glendon. Political culture and judicial behavior.: A direct observational study. Lanham, MD: University Press of America, 1985.

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19

Branch, Alberta Curriculum. Design studies: Course of studies. --. Edmonton, Alta: Alberta Education, Curriculum Branch, 1993.

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20

Instrumentation design studies. Boca Raton, FL: CRC Press, 2010.

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21

Doebelin, Ernest O. Instrumentation design studies. Boca Raton, FL: CRC Press, 2010.

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22

Dresser, Christopher. Studies in design. London: Studio Editions, 1988.

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23

Dresser, Christopher. Studies in design. London: Studio Editions, 1988.

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24

Patil, Ganapati P. Composite Sampling: A Novel Method to Accomplish Observational Economy in Environmental Studies. Boston, MA: Springer Science+Business Media, LLC, 2011.

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25

Observational Studies. Springer, 2010.

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26

Rosenbaum, Paul R. Observational Studies. Springer London, Limited, 2013.

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27

Design Of Observational Studies. Springer, 2009.

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28

Rosenbaum, Paul R. Design of Observational Studies. Springer, 2020.

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29

Design Of Observational Studies. Springer, 2012.

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30

Rosenbaum, Paul R. Design of Observational Studies. Springer International Publishing AG, 2021.

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31

Design of Observational Studies. Springer London, Limited, 2009.

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32

Cochran, William G. Planning and Analysis of Observational Studies. Wiley & Sons, Incorporated, John, 2009.

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33

Taback, Nathan. Design and Analysis of Experiments and Observational Studies Using R. Taylor & Francis Group, 2022.

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34

Taback, Nathan. Design and Analysis of Experiments and Observational Studies Using R. Taylor & Francis Group, 2022.

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35

Taback, Nathan. Design and Analysis of Experiments and Observational Studies Using R. Taylor & Francis Group, 2022.

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36

Hackshaw, Allan. Concise Guide to Observational Studies in Healthcare. Wiley & Sons, Incorporated, John, 2014.

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37

Hackshaw, Allan. Concise Guide to Observational Studies in Healthcare. Wiley & Sons, Incorporated, John, 2015.

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38

Hackshaw, Allan. Concise Guide to Observational Studies in Healthcare. Wiley & Sons, Incorporated, John, 2014.

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39

Hackshaw, Allan. Concise Guide to Observational Studies in Healthcare. Wiley & Sons, Limited, John, 2013.

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40

Hackshaw, Allan. Concise Guide to Observational Studies in Healthcare. Wiley & Sons, Incorporated, John, 2015.

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41

Hackshaw, Allan. A Concise Guide to Observational Studies in Healthcare. Wiley-Interscience, 2015.

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42

Observational Studies in a Learning Health System: Workshop Summary. National Academies Press, 2013.

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43

Alper, Joe, Claudia Grossmann, Roundtable on Value and Science-Driven Health Care, Institute of Medicine, and A Learning Health System Activity. Observational Studies in a Learning Health System: Workshop Summary. National Academies Press, 2013.

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44

Alper, Joe, Claudia Grossmann, Roundtable on Value and Science-Driven Health Care, Institute of Medicine, and A Learning Health System Activity. Observational Studies in a Learning Health System: Workshop Summary. National Academies Press, 2013.

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45

Alper, Joe, Claudia Grossmann, Roundtable on Value and Science-Driven Health Care, Institute of Medicine, and A Learning Health System Activity. Observational Studies in a Learning Health System: Workshop Summary. National Academies Press, 2013.

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46

Ray, Sumantra (Shumone), Sue Fitzpatrick, Rajna Golubic, Susan Fisher, and Sarah Gibbings, eds. Navigating research methods: quantitative and clinical/epidemiological methods. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780199608478.003.0003.

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Анотація:

This chapter focuses on various types of study design used in clinical and healthcare research with an emphasis on observational studies whilst randomised controlled trials are explained in Chapter 15. Within observational studies, the distinction between descriptive and analytical studies is made and different sources of error in epidemiological studies are reviewed. Main features, advantages and disadvantages of analytical observational studies are described for the following designs: ecological studies, cohort studies, case-control studies and cross-sectional studies. A brief overview of experimental studies is also given. Measures of disease occurrence (prevalence, cumulative incidence, incidence rate) as well as effect measures (1.difference measures, ie. attributable risk, and 2. ratio measures, i.e. relative risk, odds ratio, relative risk reduction, attributable fraction) are reviewed. The chapter also presents major characteristics of meta-analysis.

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47

Silman, Alan J., Gary J. Macfarlane, and Tatiana Macfarlane. Epidemiological Studies: A Practical Guide. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780198814726.001.0001.

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Анотація:

This volume provides a practical, hands on guide to the design, planning, conduct, analysis, and interpretation of epidemiological studies. The learning points are applicable to all human studies of health and disease that require the collection and analysis of data to answer questions on disease risk, health outcomes, and the effects of interventions in ‘real world’ populations. It summarizes the main study designs used in epidemiological from purely quantitative studies to assess incidence and prevalence, to the range of observational studies used in the modern practice of epidemiology. A substantial section is devoted to the practical aspects of conduct of epidemiological studies, balancing scientific quality with practicality: the latter covering issues such as costs and ethics. This book also provides a detailed menu of activities that takes the investigator through all the necessary steps following the collection of individual subject data through to generating the statistically robust results necessary to reach conclusions about the questions asked. It provides insights into how to use existing data (secondary data analysis) to answer epidemiological questions, an increasing activity in this era of ‘big data’. Similarly, with a growing epidemiological literature, with multiple studies seemingly addressing the same question, the volume explores how practically to synthesize the results of such multiple investigations and the role of meta-analysis. The book’s ultimate goal is to provide a practical toolkit to enable the successful completion of questions appropriate for applying epidemiological methods.

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48

Westreich, Daniel. Epidemiology by Design. Oxford University Press, 2019. http://dx.doi.org/10.1093/oso/9780190665760.001.0001.

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Анотація:

As the cornerstone science of public health, evidence-based medicine, and comparative effectiveness research, a clear understanding of study designs is central to the study of epidemiology. Causal inference is increasingly being understood as the theoretical foundation underlying epidemiologic study designs and the science as a whole. This textbook takes a causal approach to traditional introductory epidemiology, through the organizing principle of study designs and the lens of modern causal inference approaches (potential outcomes, counterfactuals, identification conditions). The intended audience is first-year graduate students and advanced undergraduates in epidemiology and allied fields more broadly. Section I introduces measures of prevalence and incidence (survival curves, risks, rates, odds) and measures of contrast (differences, ratios), the fundamentals of causal inference, and principles of diagnostic testing, screening, and surveillance. Section II describes three key study designs through the lens of causal inference: randomized trials, prospective observational cohort studies, and case-control studies. For each, the author discusses logistics and conduct, advantages and disadvantages including biases, basic approaches to analysis, and briefly reviews several additional study designs. Section III extends material in previous sections, moving from concerns about internal validity (within a sample) to questions of external validity and population impact. This book provides new students with a rigorous foundation in epidemiologic methods and an introduction to methods and thinking in causal inference, serving as an excellent foundation for further study of the field.

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49

Center, Langley Research, ed. Conceptual radiometer design studies for earth observations from low earth orbit. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1994.

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50

Dahm, Philipp, ed. 50 Studies Every Urologist Should Know. Oxford University Press, 2021. http://dx.doi.org/10.1093/med/9780190655341.001.0001.

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Анотація:

This book describes the most influential studies that have shaped today’s clinical practice of urology. Its scope spans the spectrum of clinical urology, including genitourinary oncology (prostate, renal, bladder, and testis cancer), stone disease, benign prostatic hyperplasia, erectile dysfunction, and female urology. Most included studies are landmark randomized controlled trials related to questions of therapy, but the selection also includes prospective observational cohort studies as well as some case series that have resulted in paradigm-shifting changes in patient management. Each individual study is succinctly presented using a standardized format that focuses on the most important aspects relating to its design and main findings. This is followed by a summary of relevant, closely related studies as well as a brief critique of each study’s limitations. The evidence-based format of this book is further underscored by the frequent reference to relevant clinical practice guidelines. Each chapter closes with a clinical scenario that presents a management question for which an expert clinician proposes an answer based on the current best evidence.

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