UCLA Fielding School of Public Health scholar’s new textbook equips statisticians and students to design studies using the open-source software language “R”

Study design, data analysis, visualization, statistical computing and modeling. The software R — a scientific standard for more than three decades that is widely available as free, open-source software — is a programming language that can make all of these possible.

For professional researchers and graduate students interested in developing the skills needed to design studies using R, there’s a new textbook titled Power and Sample Size in R, by Dr. Catherine Crespi, professor and vice-chair of the Department of Biostatistics at the UCLA Fielding School of Public Health.

The new textbook takes a broad and deep approach to guiding readers through calculations for a wide variety of study outcomes and designs. The textbook has an intended audience of working investigators, statisticians, and students, and an online companion website is available which includes numerous exercises for instructors and students to explore and hone their skillsets.

“I saw the need for a textbook for statisticians and students that both explained power and sample size concepts and also showed how you can do the calculations in software,” said Crespi, a professor and biostatistician whose work on the prevention and control of cancer and other chronic diseases, for example, relies on statistical models. “The goal was to produce a guide for students and working professionals on how to design a study — in particular, how many subjects we need to have in a study, so that when it’s complete, the data will be useful and help meet the study’s stated objectives.”

Biostatisticians apply their expertise in data analysis and statistical modeling and methods to public health issues, teaming with subject-matter experts on a wide range of health topics, ranging from drug development to infectious disease outbreaks, to ensure that meaningful information is captured and that scientifically valid conclusions follow from the data.

Crespi, a fellow of the American Statistical Association who has served on review panels for the National Institutes of Health, said this new work is also designed to help bridge the gap between biostatisticians and other experts, as well as serve as a resource for teachers and students. Only a basic proficiency in the R software is necessary, she said.

“This is a really broad and deep approach that covers a lot of subjects with statistical rigor,” said Crespi. "One of the advantages of the software platform is that R is open-source; anyone can download the software and use it.”

Key features of the textbook include:

• Explanations of sample size calculation for a wide variety of study designs and outcomes
• Suitable for both students and experienced researchers
• Highlights key factors influencing power and provides
• Practical tips for designing real studies
• Extensive examples with R code
• More resources on the companion website

Collaborators on the R software package include Dr. Kristen McGreevy, who earned a PhD from UCLA Fielding’s Department of Biostatistics in 2024, and current biostatistics PhD student Zichen Liu.