Taback Nathan. Design and Analysis of Experiments and Observational Studies Using R

Chapman and Hall/CRC Press, 2022. — 292 p. — ISBN: 978-1-003-03369-1.Introduction to Design and Analysis of Scientific Studies exposes undergraduate and graduate students to the foundations of classical experimental design and observational studies through a modern framework - The Rubin Causal Model. A causal inference framework is important in design, data collection, and analysis since it provides a framework for investigators to readily evaluate study limitations and draw appropriate conclusions. R is used to implement designs and analyze the data collected.Features- Classical experimental design with an emphasis on computation using tidyverse packages in R.
- Applications of experimental design to clinical trials, A/B testing, and other modern examples.
- Discussion of the link between classical experimental design and causal inference.
- The role of randomization in experimental design and sampling in the big data era.
- Exercises with solutions.Instructor slides in RMarkdown, a new R package will be developed to be used with the book, and a bookdown version of the book will be freely available. The proposed book will emphasize ethics, communication, and decision-making as part of the design, data analysis, and statistical thinking.True PDF