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Analysis of Epidemiologic Data Using R [electronic resource] / by Robert Hirsch.

By: Contributor(s): Material type: TextSeries: Synthesis Lectures on Mathematics & StatisticsPublisher: Cham : Springer Nature Switzerland : Imprint: Springer, 2024Edition: 1st ed. 2024Description: X, 109 p. 76 illus., 29 illus. in color. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783031419140
Subject(s): Additional physical formats: Printed edition:: No title; Printed edition:: No title; Printed edition:: No titleLOC classification:
  • QH323.5
Online resources:
Contents:
Introduction to R -- Measures of Disease Frequency -- Measures of Association -- 2x2 Tables -- Life Tables -- Control of Confounding.
In: Springer Nature eBookSummary: This book addresses the description and analysis of occurrence data frequently encountered in epidemiological studies. With the occurrence of Covid-19, people have been exposed to the analysis and interpretation of epidemiological data. To be informed consumers of this information, people need to understand the nature and analysis of these data. Effort is made to emphasize concepts rather than mathematics. Subjects range from description of the frequencies of disease to the analysis of associations between the occurrence of disease and exposure. Those analyses begin with simple associations and work up to complex relationships that involve the control of extraneous characteristics. Analyses rely on the statistical software R, which is freeware in wide use by professional epidemiologists and other scientists.
Item type: List(s) this item appears in: Titluri cărți electronice Springer Nature 2025 (10631 titluri)
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Introduction to R -- Measures of Disease Frequency -- Measures of Association -- 2x2 Tables -- Life Tables -- Control of Confounding.

This book addresses the description and analysis of occurrence data frequently encountered in epidemiological studies. With the occurrence of Covid-19, people have been exposed to the analysis and interpretation of epidemiological data. To be informed consumers of this information, people need to understand the nature and analysis of these data. Effort is made to emphasize concepts rather than mathematics. Subjects range from description of the frequencies of disease to the analysis of associations between the occurrence of disease and exposure. Those analyses begin with simple associations and work up to complex relationships that involve the control of extraneous characteristics. Analyses rely on the statistical software R, which is freeware in wide use by professional epidemiologists and other scientists.

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