Medoids: Simulated Cluster Medoids Data for 'EC_patient'

In Lauren-Eyler/EconomicClusters: Population-Specific Economic Groups Defined by Few Asset Variables

Simulated Cluster Medoids Data for 'EC_patient'

Description

This data set represents a potential data frame of cluster medoids' responses to selected asset variables, as generated by the function 'EconomicClusters'.

Usage

data(Medoids)

Format

A data frame with 10 observations on 5 variables. To simplify the analysis for the sake of demonstration, this data frame was generated manually to mimic the medoids selected by the 'EconomicClusters' algorithm from 'data_for_EC', with variables as follows:

V2

a binary variable with levels 0, 1

V5

a binary variable with levels 0, 1

V6

a binary variable with levels 0, 1

V9

a categorical variable with levels 1 to 4

V11

a categorical variable with levels 1 to 4

Details

The data frame 'Medoids' represents households within a simulated population selected as cluster medoids by the 'EconomicClusters' algorithm. The columns describe the medoids' responses to the 5 variables selected by the model. This data frame was generated manually.

Source

This data set was simulated by the package authors in order to demonstrate the functionality of the 'EconomicClusters' package.

See Also

EconomicClusters

Examples

#We previously defined an economic clustering model for our population using 'EconomicClusters'.
#We saved a data frame containing the responses to the economic questions 
#selected by the model for the cluster medoids as 'Medoids'.
#We have since collected trauma registry data for 250 patients 
#and asked them the 5 economic questions selected by the model.
#Data set 'Pts' contains the new patients' responses to these five questions.
#We now want to know which economic cluster each patient belongs in.

data(Pts)
data(Medoids)
data(Pop)
data(PopClusters)
Pt_clust<-EC_patient(Pts, Medoids, Pop, PopClusters)
#number of patients per cluster:
table(Pt_clust)

#We now have a vector of patient cluster membership

Lauren-Eyler/EconomicClusters documentation built on March 22, 2022, 1:21 a.m.