simdata.red: Simulated toy data with two groups to test the mbclusterwise...

In mbclusterwise: Clusterwise Multiblock Analyses

Description

This data frame is a toy example with a limited number of observations extracted from the data simdata given in the plspm package. These are simulated data organized in two clusters showing two different local regression models.

Usage

data(simdata.red)

Format

A data frame of simulated data with 40 observations on the following 14 variables.

mv1

first variable of the block Price Fairness (X_1)

mv2

second variable of the block Price Fairness (X_1)

mv3

third variable of the block Price Fairness (X_1)

mv4

fourth variable of the block Price Fairness (X_1)

mv5

fifth variable of the block Price Fairness (X_1)

mv6

first variable of the block Quality (X_2)

mv7

second variable of the block Quality (X_2)

mv8

third variable of the block Quality (X_2)

mv9

fourth variable of the block Quality (X_2)

mv10

fifth variable of the block Quality (X_2)

mv11

first variable of the block Customer Satisfaction (Y)

mv12

second variable of the block Customer Satisfaction (Y)

mv13

third variable of the block Customer Satisfaction (Y)

References

Esposito Vinzi, V., Ringle, C., Squillacciotti, S. and Trinchera, L. (2007) Capturing and treating unobserved heterogeneity by response based segmentation in PLS path modeling. A comparison of alternative methods by computational experiments. Working paper, ESSEC Business School.

Examples

  data(simdata.red)
  simdata.red
  Data.X <- simdata.red[c(1:15, 21:35), 1:10]
  Data.Y <- simdata.red[c(1:15, 21:35), 11:13]  

mbclusterwise documentation built on May 2, 2019, 9:19 a.m.