» Software

This page provides an overview of the most common software programmes available for performing QCA. While the main advantages and disadvantages of each solution in terms of basic functionality are listed, all programmes also feature additional, and often unique, procedures. Generally, software programmes with a graphical user interface (GUI) are more user-friendly, but limited in their capabilities (fs/QCA, KirqST, Tosmana). Command line interface (CLI) software, in contrast, has a much steeper learning curve because it requires programming, but it is usually also more flexible and powerful (R packages QCA and QCA3, Stata package fuzzy).

All software solutions are provided free of charge and their developers have invested much time and effort into programming them. If you make use of a programme, we would thus ask you to acknowledge this by citing it in your work. An appropriate citation is provided below the software screenshots.

Six programmes are introduced:

GUI Software	CLI Software
fs/QCA, Version 2.5	R QCA, Version 1.0-5
KirqST, Version 2.09	R QCA3, Version 0.0-5
Tosmana, Version 1.3.2.0	Stata fuzzy, Version st0140_2

fs/QCA, Version 2.5

fs/QCA is the most popular QCA software (about 80% "market share"). It has been in existence since 1992 (predecessor QCA 3.0) and has been developed by Charles Ragin, Sean Davey and Kriss Drass. The programme can be downloaded from Charles Ragin's website. The manual of fs/QCA can be found here.

Advantages	Disadvantages
●  graphical user interface	●  only operates on Windows
●  csQCA (tQCA) and fsQCA	●  no mvQCA
●  intermediate solutions	●  no Venn diagramms for csQCA
●  analysis of necessity relations (manual)	●  no case identification in truth tables
●  parameters of fit	●  no statistical procedures
●  scatterplots for fuzzy set relations
Screenshots

Please cite as: Ragin, Charles and Sean Davey. 2009. fs/QCA, Version 2.5. Tucson: University of Arizona.

R Package "QCA", Version 1.0-5

QCA is a package for the R environment for statistical computing and graphics. It has existed since 2006, but has been released in April 2012 in a completely revised version. The authors are Adrian Duşa and Alrik Thiem. The package can be installed from within R or be downloaded from CRAN. The manual of QCA can be found here. The authors are also in the process of providing video tutorials on how to use the QCA package. The first two videos in this series deal with set operations in R and the usage of the QCA package documentation. They can be watched on YouTube.

Advantages	Disadvantages
●  platform-independent	●  no graphical user interface (package QCAGUI outdated)
●  csQCA, tQCA, mvQCA, fsQCA	●  no statistical procedures
●  extremely efficient eQMCC algorithm	●  no internal functionality for Venn diagrams
●  intermediate solutions for all QCA variants	●  no internal functionality for fuzzy-set scatterplots
●  derivation of non-minimal solutions
●  analysis of necessity relations (automated)
●  flexible fuzzy-set calibration
●  cluster-analysis for csQCA/mvQCA thresholds
●  automated Boolean calculations for PIs
●  PI chart and simplifying assumptions
●  factorization of solutions
●  extensive documentation
Screenshots

Please cite as: Duşa, Adrian and Alrik Thiem. 2013. QCA: Qualitative Comparative Analysis. R Package Version 1.0-5.

R Package "QCA3", Version 0.0-5

QCA3 is the second package for the R environment for statistical computing and graphics. It has been first released in 2009 by Ronggui Huang. The package can be installed from within R or be downloaded from CRAN. The manual of QCA3 can be found here.

Advantages	Disadvantages
●  platform-independent	●  no graphical user interface
●  csQCA, tQCA, mvQCA, fsQCA	●  no internal functionality for Venn diagrams
●  cluster-analysis for csQCA/mvQCA thresholds	●  no automated procedure for intermediate solutions
●  statistical procedures
●  (contradictory) simplifying assumptions
●  scatterplots for fuzzy-set relations
●  PI charts
Screenshots

Please cite as: Huang, Ronggui. 2012. QCA3: Yet another Package for Qualitative Comparative Analysis. R Package Version 0.0-5.

STATA Package "fuzzy", st0140_2

fuzzy is a package for the commercial statistical software STATA. It has been developed with a strong orientation towards the incorporation of probabilistic procedures. The authors are Kyle Longest and Stephen Vaisey.

Advantages	Disadvantages
●  platform-independent	●  requires commercial software STATA
●  various statistical tests	●  no mvQCA
●  flexible calibration (set-normalizing, "direct"/"indirect")	●  no intermediate solutions
●  scatterplot for fuzzy-set relations
Screenshots

Please cite as: Longest, Kyle C., and Stephen Vaisey. 2008. "fuzzy: A program for Performing Qualitative Comparative Analyses (QCA) in Stata." Stata Journal 8 (1):79-104.

KirqST, Version 2.09

KirqST is a standalone, cross-platform GUI program which is based on libfsqca, a cross-platform, reusable library. The authors are Christopher Reichert and Claude Rubinson. The programme can be downloaded from the Kirq website.

Advantages	Disadvantages
●  supports Windows, OSX, Linux	●  no mvQCA
●  graphical user interface	●  no graphical capabilities
●  analysis of necessity relations (automated)	●  no functionality for set calibration
●  truth table sorting and filtering
●  flexible truth table coding
●  identification of (in)consistent cases
●  multiple sessions at once
Screenshots

Please cite as: Reichert, Christopher and Claude Rubinson. 2013. KirqST, Version 2.09. Houston, TX: University of Houston-Downtown.

Tosmana, Version 1.3.2.0

Tosmana has been the first programme for the analysis of multi-value data and is the second most popular QCA software. Its author is Lasse Cronqvist. The latest version is now platform-independent and can be downloaded from the Tosmana website. The manual of Tosmana can be found here.

Advantages	Disadvantages
●  graphical user interface	●  no fsQCA
●  csQCA and mvQCA (also multi-level outcomes)	●  no intermediate solutions
●  complex and parsimonious solutions	●  no analysis of necessity relations
●  elaborate Venn diagrams for csQCA	●  no parameters of fit
●  cluster-analysis for setting of threshold	●  no Venn diagramms for mvQCA
●  fast graph-based minimzation algorithm	●  no Boolean calculations for mvQCA
●  identification of simplifying assumptions
●  factorization of solutions
●  PI charts
●  Boolean calculator
Screenshots

Please cite as: Cronqvist, Lasse. 2011. Tosmana: Tool for Small-N Analysis, Version 1.3.2.0. Trier: University of Trier.