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Design and Analysis of Experiments and Observational Studies using R

Nathan Taback
€107.99
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A01=Nathan Taback
ANOVA Identity
ANOVA Table
Author_Nathan Taback
Category=PBT
causal inference methods
CDF
clinical trial methodology
Data Frame
Data Set
Design Scientific Studies
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eq_isMigrated=2
eq_nobargain
experimental statistics education
Experimental Unit
Graeco Latin Square Design
Half Normal Plot
Ignorable Treatment Assignment
Latin Square
Latin Square Design
modern causal analysis with R
Non-centrality Parameter
Normal Quantile Plot
Permuted Block Randomization
Propensity Score
Propensity Score Matching
Propensity Score Model
Propensity Score Quintile
Propensity Score Subclass
Random Assignments
Randomized Block Design
simulation in statistics
statistical computing
tidyverse data analysis
Treatment Assignment
Unpaired Design
Unreplicated Factorial Designs

Product details

  • ISBN 9780367456856
  • Weight: 360g
  • Dimensions: 156 x 234mm
  • Publication Date: 27 Apr 2022
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Hardback
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Description

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 analyse 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 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 design, data analysis, and statistical thinking.
About Nathan Taback

Nathan Taback is Associate Professor of Statistics and Data Science at University of Toronto.

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