qualitative or mixed data analysis

LinkedIn даёт пакет для такого анализа.
#Rstats #research My brief survey of R packages for qualitative (or mixed) data analysis. http://qr.ae/6auZw

May be lme4 will be useful
http://lme4.r-forge.r-project.org/lMMwR/lrgprt.pdf

Javier, I appreciate the suggestion and the link. In my post, I've tried to limit the discussion to R packages that are much more focused on qualitative data analysis than many others. I understand that "lme4" and many other packages contain functionality that deals with qualitative (in a form of categorical) or mixed data, but I was trying to limit the scope of the material for better focus. More importantly, mixed-effects modeling is IMHO inherently quantitative approach. Nevertheless, this is an interesting topic, which I plan to become acquainted more with in the future. Thank you again and feel free to connect!

Check also this package: http://factominer.free.fr/advanced-methods/multiple-factor-analysis.html

Ahmed, I'm aware of "factominer" and some other FA packages. However, I tend to think of them mostly as packages for quantitative data analysis, despite their support for categorical data. Please see my points in the comment for Javier above. Anyway, I appreciate your comment.

Tutorials from Universities Around the World

Online tutorials for R programming, Statistics and Graphic

Here is a list of FREE R tutorials hosted in official website of universities around the world. The tutorials are listed  in no particular order, actually based on when I have discovered it. They will be categorised soon. Please kindly suggest me other university-hosted online R tutorials by email to me@pairach.com.

1. University of California at Davis,
   Getting Started with the R Data Analysis Package
   by Professor Norm Matloff
2. Clarkson University,
   R Tutorial
   by Kelly Black
3. York University,
   Getting started with R
4. University of Waterloo
   R Tutorial For A WINDOWS Environment (Windows, Unix)
5. University of California at Los Angles, UCLA,
   Resources to help you learn and use R
6. University of California at Riverside.
   Programming in R
7. University of Illinois,
   A Brief Introduction to R
8. University of Texas at Austin,
   R Tutorial Videos
   by Brandon K. Vaughn
9. University of California at Berkeley,
   An Introduction to R (PDF)
   by Phil Spector
10. University of California at Santa Babara,
    R Programming Resource Centre
    by National Center for Ecological Analysis and Synthesis
11. Chiang Mai University,
    Econometrics with R (in Thai)
    by Pairach Piboonrungroj.
12. University of Carnegie Mellon,
    A Tutorial: Some Fundamentals of R.
    by Bruce E. Trumbo
13. University of Illinois State,
    R Tutorial.
    by Dong-Yun Kim
14. University of MacMaster,
    Introduction to the R Statistical Computing Environment.
    by John Fox.
15. University of Princeton,
    Introducing R.
    by Germán Rodríguez
16. University of Amsterdam,
    How to draw graphs with R,  [Graphics]
    by A.M. (Angelos-Miltiadis) Krypotos
17. University of North Texas,
    Do it yourself – Introduction to R [Intro]
18. University of Warwick,
    R programming page [Biosciences: Molecular Organisation and Assembly in Cells]
    by Peter Cock.
19. University of Illinois at Urbana-Champaign
    R tutorial for Applied Econometrics
    by Prof. Roger Koenker
    
20. Coastal Carolina University
    R tutorials [General]
    by  William B. King
21. University of Colorado Denver
    R Tutorial [General]
    by  Stephanie Santorico and Mark Shin
22. Stanford School of Medicine (Biomedical Informatics)
    R Tutorial [VDO on Introduction + Translational Bioinformatics]
23. Harding University
    Producing Simple Graphs with R [basic graphic e.g., line, bar, hist, line]
    by Frank McCown
24. University of Kentucky, Department of Statistics
    Use Software R to do Survival Analysis and Simulation [pdf]
    by Mai Zhou

R ссылки

.ру

• cсылки ин-та южных морей
• Статистика с большой буквы или R
• Rусский на вордпресе

.не.ру

• revolutionanalytics
• quickR for SPSS and others pax users
• r-statistics.com
• R bloggers
• An R Introduction to Statistics

R ссылки и статистика вообще

В другом блоге написал о колмогоровской сложности, это меня занимает в связи с тремя сёстрами.

Прочитал хорошую идеологическую заметку о неправильном понимании статистики на Кошках, кстати рекомендую подписаться, дяденька пишет оч душевно и понятно + великолепное владение материлом.

И наконец ссылки, вписанные в сравнение R и МатЛаба.