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Description

Tools for the Analysis of Clustered Data in QCA.

Clustered set-relational data in Qualitative Comparative Analysis (QCA) can have a hierarchical structure, a panel structure or repeated cross sections. 'QCAcluster' allows QCA researchers to supplement the analysis of pooled the data with a disaggregated perspective focusing on selected partitions of the data. The pooled data can be partitioned along the dimensions of the clustered data (individual cross sections or time series) to perform partition-specific truth table minimizations. Empirical researchers can further calculate the weight that each partition has on the parameters of the pooled solution and the diversity of the cases under analysis within and across partitions (see <https://ingorohlfing.github.io/QCAcluster/>).

QCAcluster

2021-10-22

Contributors

Three people have contributed to QCAcluster. In alphabetical order:

Description of package

Clustered data can take different forms in empirical research. The data might have a hierarchical structure (lower-level units nested in higher-level units); we might have multiple units nested in time (panel data); or the combination of both. The R package QCAcluster includes multiple tools for the analysis of clustered data in Qualitative Comparative Analysis. The use of the tools promises insights that would go unnoticed in a pooled analysis ignoring the clusters in the data.

This is work in progress. You can download the development version 0.9.0.

devtools::install_github("ingorohlfing/QCAcluster")

Work on the package was funded by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program (grant agreement number 638425, Enhanced Qualitative and Multimethod Research).

Metadata

Version

0.1.0

License

Unknown

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