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Providing complete coverage of advanced research methods and their implementation in
R to increase students' confidence with programming techniques and their application to new situations and problems.
List of contents
- 1: Introduction
- 2: Introduction to the R environment
- 3: Cleaning and preparing data for analysis
- 4: Statistical tests as linear models
- 5: Power analysis
- 6: Meta-analysis
- 7: Mixed-effects models
- 8: Stochastic methods
- 9: Non-linear curve fitting
- 10: Fourier analysis
- 11: Multivariate t-tests
- 12: Structural equation modelling
- 13: Multidimensional scaling and k-means clustering
- 14: Multivariate pattern analysis
- 15: Correcting for multiple comparisons
- 16: Signal detection theory
- 17: Bayesian statistics
- 18: Plotting graphs and data visualisation
- 19: Reproducible data analysis
About the author
Daniel H. Baker is a Senior Lecturer at the University of York. He has taught research methods for many years in the Department of Psychology, and also made contributions to the statistical literature on power analysis and multivariate methods. He studies human visual perception, with a particular emphasis on binocular vision, using a range of quantitative techniques including psychophysics, neuroimaging and computational modelling. In 2016 he was awarded the David Marr medal by the Applied Vision Association in recognition of his research contributions. He has a particular interest in making research more open, not only by sharing code and data, but also by making analysis techniques more accessible and easy to use.
Summary
Providing complete coverage of advanced research methods and their implementation in R to increase students' confidence with programming techniques and their application to new situations and problems.
Additional text
If I were to summarize my thoughts on Research Methods using R in one sentence, I would say that this book is a well-written, compact introductory synthesis of advanced statistical techniques....This book serves as excellent starting material for students, but as mentioned earlier, lecturers may also find it useful.
