partition_div {QCAcluster}

Diversity of cases belonging to the same partition of the pooled data

Description

partition_div calculates the diversity of cases that belong to the same partition of the clustered data (a time series; a cross section; etc.). Diversity is measured by the number of truth table rows that the cases of a partition cover. partition_div calculates the partition diversity for all truth table rows and for the subsets of consistent and inconsistent rows.

Usage

partition_div(dataset, units, time, cond, out, n_cut, incl_cut)

Arguments

dataset

Calibrated pooled dataset that is partitioned and minimized for deriving the pooled solution.

units

Units defining the within-dimension of data (time series)

time

Periods defining the between-dimension of data (cross sections)

cond

Conditions used for the pooled analysis

out

Outcome used for the pooled analysis

n_cut

Frequency cut-off for designating truth table rows as observed in the pooled data

incl_cut

Inclusion cut-off for designating truth table rows as consistent in the pooled data

Value

A dataframe presenting the diversity of cases belonging to the same partition with the following columns:

• type: The type of the partition. pooled are rows with information on the pooled data; between is for cross-section partitions; within is for time-series partitions.

• partition: Specific dimension of the partition at hand. For between-dimension, the unit identifiers are included here (argument units). For the within-dimension, the time identifier are listed (argument time). The entry is - for the pooled data without partitions.

• diversity: Count of all truth table rows with at least one member belonging to a partition.

• diversity_1: Count of consistent truth table rows with at least one member belonging to a partition.

• diversity_0: Count of inconsistent truth table rows with at least one member belonging to a partition.

• diversity_per: Ratio of the value for diversity and the total number of truth table rows from pooled data (diversity value for pooled data).

• diversity_per_1: Ratio of the value for diversity_1 and the total number of consistent truth table rows from pooled data (diversity_1 value for pooled data).

• diversity_per_0: Ratio of the value for diversity_0 and the total number of inconsistent truth table rows from pooled data (diversity_0 value for pooled data).

Examples

data(Schwarz2016)
Schwarz_diversity <- partition_div(Schwarz2016, 
units = "country", time = "year", 
cond = c("poltrans", "ecotrans", "reform", "conflict", "attention"), 
out = "enlarge", 1, 0.8)