Data Analysis Using R Programming

  • Bertram K. C. Chan
Part of the Advances in Experimental Medicine and Biology book series (AEMB, volume 1082)


Beginning R

R is an open-source, freely available, integrated software environment for data manipulation, computation, analysis, and graphical display. The R environment consists of
  • *a data handling and storage facility,

  • *operators for computations on arrays and matrices,

  • *a collection of tools for data analysis

  • *graphical capabilities for analysis and display, and

  • *an efficient, and continuing developing programming algebra-like programming language which consists of loops, conditionals, user-defined functions, and input and output capabilities.

Many R programs are available for biostatistical analysis in Genetic Epidemiology. Typical examples are shown.


R environment R as a calculator R graphics R in statistics R in data analysis in human genetic epidemiology Function data.entry() Function source() Spreadsheet interface in R plot() function 

Special References

  1. Aragon TJ (2011) Applied epidemiology using R (epir). UC Berkeley School of Public Health, and San Francisco Department of Public Health, BerkeleyGoogle Scholar
  2. BMI Notes (2012) Body mass index.
  3. Centers for Disease Control and Prevention (2005) Antiretroviral postexposure Prophylaxis after sexual, injection-drug use, or other nonoccupational exposure to HIV in the United States: recommendations from the U.S. Department of Health and Human Services. MMWR Recomm Rep 54(RR-2):1–20 Available from: Scholar
  4. CRAN, The comprehensive R archive network:
  5. Dalgaard P (2002) Introductory statistics with R, Springer statistics and computing series, Springer, New YorkGoogle Scholar
  6. Daniel WW (2005) Biostatistics – a foundation for analysis in the health sciences. Wiley, New YorkGoogle Scholar
  7. Everitt BS, Hothorn T (2006) A handbook of statistical analysis using R. Chapman & Hall/CRC, Boca RatonCrossRefGoogle Scholar
  8. Teetor P (2011) R Cookbook. O’Reilly Media, SebastopolGoogle Scholar
  9. Venables WN, Smith DM, and the R Development Core Team (2004) An introduction to R. Network Theory, Ltd., BristolGoogle Scholar
  10. Virasakdi C (n.d.) Analysis of epidemiological data using R and Epicalc. Epidemiology unit, Prince of Songkla University, Thailand: Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Bertram K. C. Chan
    • 1
  1. 1.Epidemiology and BiostatisticsLoma Linda University School of Medicine and Public HealthSunnyvaleUSA

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