Utvidet returrett til 31. januar 2025

Quantitative Epidemiology

Om Quantitative Epidemiology

This book is designed to train graduate students across disciplines within the fields of public health and medicine, with the goal of guiding them in the transition to independent researchers. It focuses on theories, principles, techniques, and methods essential for data processing and quantitative analysis to address medical, health, and behavioral challenges. Students will learn to access to existing data and process their own data, quantify the distribution of a medical or health problem to inform decision making; to identify influential factors of a disease/behavioral problem; and to support health promotion and disease prevention. Concepts, principles, methods and skills are demonstrated with SAS programs, figures and tables generated from real, publicly available data. In addition to various methods for introductory analysis, the following are featured, including 4-dimensional measurement of distribution and geographic mapping, multiple linear and logistic regression, Poisson regression, Cox regression, missing data imputing, and statistical power analysis.

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  • Språk:
  • Engelsk
  • ISBN:
  • 9783030838546
  • Bindende:
  • Paperback
  • Sider:
  • 336
  • Utgitt:
  • 24. februar 2023
  • Utgave:
  • 12021
  • Dimensjoner:
  • 234x156x25 mm.
  • Vekt:
  • 550 g.
  • BLACK NOVEMBER
  På lager
Leveringstid: 4-7 virkedager
Forventet levering: 5. desember 2024

Beskrivelse av Quantitative Epidemiology

This book is designed to train graduate students across disciplines within the fields of public health and medicine, with the goal of guiding them in the transition to independent researchers. It focuses on theories, principles, techniques, and methods essential for data processing and quantitative analysis to address medical, health, and behavioral challenges. Students will learn to access to existing data and process their own data, quantify the distribution of a medical or health problem to inform decision making; to identify influential factors of a disease/behavioral problem; and to support health promotion and disease prevention. Concepts, principles, methods and skills are demonstrated with SAS programs, figures and tables generated from real, publicly available data. In addition to various methods for introductory analysis, the following are featured, including 4-dimensional measurement of distribution and geographic mapping, multiple linear and logistic regression, Poisson regression, Cox regression, missing data imputing, and statistical power analysis.

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