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StatsToDo : R Explained

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Related Links:
Handling Missing Data Using R Explained Page

Introduction R Studio Data I/O
StatsToDo provides R codes in some of its pages, and this page provides an overview and orientation for using them.

The inclusion of R codes is a work in progress. Initially I aim to create resources for the more complex multivariate statistical procedures that I am unable to program myself. Eventually I aim to supplement most programs in StatsToDo with R codes and examples, using resources provided by CRAN if they are available, or to rewrite my programs using R if the progam cannot be found in CRAN. The initiative began in April 2020, so not all algorithms will be accompanied by R codes for some time

The R codes in StatsToDo are basic, simple, and the minimum necessary to conclude an initial analysis. It is aimed to create a shallow learning curve for those with no great statistical experience, to explore his/her data, and to provide the minimum results that are required by most clinical journals for publication. In most cases they merely repeat the programs written in php for the web page, and no more than a validation of the algorithm. Most experienced statisticians will find the details provided incomplete, or even insufficient, as the safeguards and complete descriptions of the results are often not provided. Although references will be provided for users to obtain further information and resources, inexperienced users are strongly urged to seek advice from experienced statisticians before drawing conclusions from the results obtained.

All data in the examples are computer generated, to demonstrate the analysis and interpretation. Although attempts were made to produce results that are plausible and easy to understand, users should realise that the data is artificial and do not represent reality. Given that I had a background in obstetrics, the examples are mostly issues in childbirth and hospitals. The interests are mostly clinical, towards classification, survey, quality control, clinical discovery and trials.


Simple codes are provided once. Those involving multiple steps are presented twice, once in total for easy copy and paste, then in individual steps with explanations and expected results.

Three colors are used, to clarify the intent of the text

  • Maroon color is used to represent R codes
  • Navy blue color is used to show results generated by R in the console
  • Black is used for explanations and descriptions

All R programs in StatsToDo assume no missing data. How to handle missing data is described in Handling Missing Data Using R Explained Page