ISCA (version 0.1.0)

ISCA_clustertable: ISCA Cluster Tables

Description

Function to create a cluster or descriptive table across iterations.

Usage

ISCA_clustertable(data, cluster_vars, draws = 500)

Value

The output is a table containing the grand mean, grand standard deviation, and cluster error for each variable and cluster. No cluster error is calculated for dichotomous variables.

Arguments

data

The dataset including all relevant variables and the random assignments from the first ISCA_random_assignments()-function.

cluster_vars

A vector specifying the variables of interest.

draws

Specification of the number of probabilistic draws. The number of draws should be equal to the number of draws specified in the first step. If not specified, the default is 500.

Examples

data(sim_data)
ISCA_step1 <- ISCA_random_assignments(data=sim_data, filter=native, 
majority_group=1, minority_group=c(0), fuzzifier = 1.5, n_clusters=4, 
draws=5, cluster_vars= c("female", "age", "education", "income"))
result_ISCA_clustertable <- ISCA_clustertable(data = ISCA_step1, 
cluster_vars = c("native", "education", "age", "female", 
"discrimination", "religiosity"), draws = 5);