Pop: Simulated DHS Population Assets Data for 'EC_patient'

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

Simulated DHS Population Assets Data for 'EC_patient'

Description

This data set was designed to represent a data frame of the DHS population responses to the asset variables selected by the 'EconomicClusters' algorithm, as generated by the function 'EconomicClusters'.

Usage

data(Pop)

Format

A data frame with 13 observations on 5 variables. To simplify the analysis for the sake of demonstration, this data frame was generated manually to match the observations in Pts who do not match cluster medoids:

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 'Pop' represents DHS population responses to the asset variables selected by the 'EconomicClusters' algorithm. Note: A real DHS dataset has many more observations than this. This data frame was generated manually to match the observations in Pts who do not match cluster medoids.

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 saved a data frame consisting of the DHS population's responses to the economic questions
#selected by the model as Pop.
#We saved a vector of the cluster membership of each DHS observation as PopClusters.
#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.