Diagnostic tool for clustered data

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Description

Function returns pooled, within, and between consistencies for an object of class "qca".

Usage

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cluster.eqmcc(results, data, outcome, unit_id, cluster_id, intermed=FALSE, sol = 1)

Arguments

results

An object of class "qca".

data

A data frame.

outcome

A character string with the name of the outcome.

unit_id

A character string with the name of the vector containing the units (i.e. countries).

cluster_id

A character string with the name of the vector containing the clustering units (i.e. years).

intermed

Logical. Use the intermediate solution?

sol

A numeric vector where the first number indicates the number of the solution according to the order in the "qca" object.

Author(s)

Ioana-Elena Oana and Juraj Medzihorsky

References

Garcia-Castro, A., Arino, M. A.. 2013. A General Approach to Panel Data Set-Theoretic Research. COMPASSS Working Paper 2013-76

See Also

eqmcc

Examples

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# Import your clustered data in the long format. 
# For example:

data(SchneiderLong)

# Get the intermediate solution:

sol_yi <- eqmcc(SchneiderLong, outcome = "EXPORT",
                conditions = c("EMP","BARGAIN","UNI","OCCUP","STOCK", "MA"),
                incl.cut1 = .9, 
                include = "?", 					   
                details = TRUE, show.cases = TRUE, dir.exp = c(0,0,0,0,0,0))

# Get pooled, within, and between consistencies for the second intermediate solution:

cluster.eqmcc(results = sol_yi, data = SchneiderLong, outcome = "EXPORT", unit_id = "COUNTRY", 
              cluster_id = "YEAR", intermed = TRUE, sol = 2)

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