R package to analyse Q methodology data

View the Project on GitHub aiorazabala/qmethod

qmethod, an R package to analyse Q methodology data

Q is a methodology to study the distinct perspectives existing within a group of people, on a topic of interest. It is used across disciplines. See further about the method in http://qmethod.org/about.


This package performs the analysis of Q methodology data. Data can be imported from a range of formats, and results can be explored and exported in multiple ways. See a graphical interface with the basic functionality and an example of what you can do with this package.

The package provides all the options for standard Q analysis, such as different extraction methods (principal components analysis and centroid factor extraction), rotation methods (none or varimax), and both forced and non-forced distributions. Manual flagging can be easily run using R code (see an example). Additional options include different correlation coefficients for the initial correlation matrix (Pearson, Spearman and Kendall) and other mathematical rotations.

A single function runs the full analysis (qmethod()). Each step can also be run separately using the corresponding functions for correlation matrix, automatic flagging, statement scores, distinguishing and consensus statements, and general factor characteristics.

Additional functions are available to import data from raw .CSV, ‘HTMLQ’ and ‘FlashQ’ .CSV files, ‘PQMethod’ .DAT files and ‘easy-htmlq’ .JSON files; to plot and summarise Q results; to import raw data from individual and multilingual .CSV files; to make printable cards; and to perform bootstrapping.

For full details about what you can do, see the package reference manual.


Here are further links to learn more about the software and about conducting Q methodology (more references in the package reference manual):


The package has been created and is maintained by Aiora Zabala, with contributions from Max Held and Frans Hermans. Further contributions are most welcome. To do so, please read the guidelines, post your suggestions on the issue tracker, or email the maintainer.

The package is free and open source. It has been thoroughly tested an validated. If you use it, please cite it in your work.

Pathway of priority developments, should resources allow (also a record of some of the previous work is here):

If you find the package and these resources useful, consider supporting maintenance and further enhancements: