Tools for the Analysis of Clustered Data in QCA
Diversity of cases belonging to the same partition of the pooled data
Generation of conservative or parsimonious solution for individual par...
Generation of intermediate solutions for individual partitions of clus...
Aggregation of individual conditions over partition-specific models
Aggregation of individual configurations over partition-specific model...
Weight of partitions for pooled solution parameters for conservative o...
Calculation of weight of partitions in pooled solution parameters for ...
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/>).
Useful links