Analysis of categorical data with R. The book presents a modern account of categorical data analysis using the popular R software. It covers recent techniques of model building and assessment for binary, multicategory, and count response variables and discusses fundamentals, such as odds ratio and probability estimation. The authors give detailed advice and guidelines on which procedures to use and why to use them. The use of R as both a data analysis method and a learning tool requiring no prior experience with R, the text offers an introduction to the essential features and functions of R. It incorporates numerous examples from medicine, psychology, sports, ecology, and other areas, along with extensive R code and output. The authors use data simulation in R to help readers understand the underlying assumptions of a procedure and then to evaluate the procedure’s performance. They also present many graphical demonstrations of the features and properties of various analysis methods. Web Resource: The data sets and R programs from each example are available at www.chrisbilder.com/categorical. The programs include code used to create every plot and piece of output. Many of these programs contain code to demonstrate additional features or to perform more detailed analyses than what is in the text. Designed to be used in tandem with the book, the website also uniquely provides videos of the authors teaching a course on the subject. These videos include live, in-class recordings, which instructors may find useful in a blended or flipped classroom setting. The videos are also suitable as a substitute for a short course.
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References in zbMATH (referenced in 10 articles , 1 standard article )
Showing results 1 to 10 of 10.
- Rydén, Jesper: On features of fugue subjects. A comparison of J. S. Bach and later composers (2020)
- Anderson-Cook, Christine M.; Myers, Kary L.; Lu, Lu; Fugate, Michael L.; Quinlan, Kevin R.; Pawley, Norma: How to host an effective data competition: statistical advice for competition design and analysis (2019)
- Chen, Yang; Meng, Xiao-Li; Wang, Xufei; van Dyk, David A.; Marshall, Herman L.; Kashyap, Vinay L.: Calibration concordance for astronomical instruments via multiplicative shrinkage (2019)
- Haag, Fridolin; Zürcher, Sara; Lienert, Judit: Enhancing the elicitation of diverse decision objectives for public planning (2019)
- Abdel Aal, Medhat M.; Saad Mowafy, Mamdouh A. Alim; Etman, Nehal: A statistical approach for understanding the plethora of miRNAs and mRNAs interplay (2018)
- Ghosh, Subir; Nyquist, Hans: Model fitting and optimal design for a class of binary response models (2016)
- Liu, Ivy: Book review of: C. R. Bilder and T. M. Loughin, Analysis of categorical data with R (2016)
- Bilder, Christopher R.; Loughin, Thomas M.: Analysis of categorical data with R (2015)
- Ngesa, Owino; Ziegler, Andreas: Book review of: C. R. Bilder and T. M. Loughin, Analysis of categorical data with R. (2015)
- Park, Taesung: Book review of: C. R. Bilder and T. M. Loughin, Analysis of categorical data with R. (2015)