Using R and R Studio for Data Management
Using R and R Studio for Data Management

Who should use this book

Those with an understanding of statistics at the level of multiple-regression analysis should find this book helpful. This group includes professional analysts who use statistical packages almost every day as well as statisticians, epidemiologists, economists, engineers, physicians, sociologists, and others engaged in research or data analysis. We anticipate that this tool will be particularly useful for sophisticated users, those with years of experience in only one system, who need or want to use the other system. However, intermediate-level analysts should reap the same benefit. In addition, the book will bolster the analytic
abilities of a relatively new user, by providing a concise reference manual and annotated examples.

Using the book

The book has two indices, in addition to the comprehensive table of contents. These include: 1) a detailed topic (subject) index in English; 2) an R command index, describing R syntax.

Extensive example analyses of data from a clinical trial are presented; see Table B.1 (p. 237) for a comprehensive list. These employ a single dataset (from the HELP study), described in Appendix B. Readers are encouraged to download the dataset and code from the book website. The examples demonstrate the code in action and facilitate exploration by the reader.

In addition to the HELP examples, a case studies and extended examples chapter utilizes many of the functions, idioms and code samples introduced earlier. These include explications of analytic and empirical power calculations, missing data methods, propensity score analysis, sophisticated data manipulation, data gleaning from websites, map making, simulation studies, and optimization. Entries from earlier chapters are cross-referenced to
help guide the reader.

Where to begin

We do not anticipate that the book will be read cover to cover. Instead, we hope that the extensive indexing, cross-referencing, and worked examples will make it possible for readers to directly find and then implement what they need. A new user should begin by reading the first chapter, which includes a sample session and an overview of the system. Experienced users may find the case studies to be valuable as a source of ideas on problem-solving in R.