Modeling binary correlated responses using SAS, SPSS and R [Documento electrónico] / Jeffrey R. Wilson, Kent A. Lorenz
Language: eng.Country: US - United States of America.Publication: Cham : Springer International Publishing, 2015Description: XXIII, 264 p. 26 il.ISBN: 978-3-319-23805-0.Series: ICSA book series in statisticsSubject - Topical Name: Estatística matemática | Métodos estatísticos | Estatística Online Resources:Click here to access onlineItem type | Current library | Collection | Call number | Copy number | Status | Date due | Barcode | |
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E-Books | Biblioteca NOVA FCT | Não Ficção | QA276 FCT 96379 (Browse shelf(Opens below)) | 1 | Available |
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QA276. FCT 94780 Statistics applied to clinical trials | QA276. FCT 95357 Sound analysis and synthesis with R | QA276 FCT 95635 Mathematics and politics, strategy, voting, power and proof | QA276 FCT 96379 Modeling binary correlated responses using SAS, SPSS and R | QA276. FCT 96485 Brief guidelines for methods and statistics in medical research | QA276 FCT 96565 Modeling and stochastic learning for forecasting in high dimensions | QA276 FCT 96571 Theory and practice of risk assessment, ICRA 5, Tomar, Portugal, 2013 |
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Statistical tools to analyze correlated binary data are spread out in the existing literature. This book makes these tools accessible to practitioners in a single volume. Chapters cover recently developed statistical tools and statistical packages that are tailored to analyzing correlated binary data. The authors showcase both traditional and new methods for application to health-related research. Data and computer programs will be publicly available in order for readers to replicate model development, but learning a new statistical language is not necessary with this book. The inclusion of code for R, SAS, and SPSS allows for easy implementation by readers. For readers interested in learning more about the languages, though, there are short tutorials in the appendix. Accompanying data sets are available for download through the book s website. Data analysis presented in each chapter will provide step-by-step instructions so these new methods can be readily applied to projects. Researchers and graduate students in Statistics, Epidemiology, and Public Health will find this book particularly useful.
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