plspm.groups {plspm} | R Documentation |
This function performs a group comparison test for comparing path coefficients between two groups
plspm.groups(x, pls, g, method = "bootstrap", reps = NULL)
x |
A numeric matrix or data frame containing the manifest variables. |
pls |
An object of class "plspm" returned by the function plspm |
g |
A factor with 2 levels indicating the groups to be compared |
method |
The method to be used in the test. Possible values are "bootstrap" or "permutation" |
reps |
An integer indicating the number of either bootstrap resamples or number of permutations. If NULL then reps =100 |
The function plspm.groups
performs a two groups comparison test in PLS-PM for comparing path coefficients between two groups. For the moment, only two methods are available: 1) bootstrap, and 2) permutation.
The bootstrap test is an adapted t-test based on bootstrap standard errors.
The permutation test is a randomization test which provides a non-parametric option.
The null and alternative hypotheses to be tested are:
H0: path coefficients are not significantly different
H1: path coefficients are significantly different
In order to use the function plspm.groups
the argument x
must be the same argument used in the function plspm
to calculate the object pls
.
An object of class "plspm.groups"
, basically a list with the following elements:
test |
Table with the results of the applied test. Includes: path coefficients of the global model, path coeffs of group1, path coeffs of group2, (absolute) difference of path coeffs between groups, and the test results with the p-value. |
global |
List with results of the inner model for the global model |
group1 |
List with results of the inner model for group1 |
group2 |
List with results of the inner model for group2 |
Gaston Sanchez
Chin, W.W. (2003) A permutation procedure for multi-group comparison of PLS models. In: Vilares, M., Tenenhaus, M., Coelho, P., Esposito Vinzi, V., Morineau, A. (Eds.) PLS and Related Methods - Proceedings of the International Symposium PLS03. Decisia, pp. 33-43.
Chin, W.W. (2000) Frequently Asked Questions, Partial Least Squares PLS-Graph. Available from:
http://disc-nt.cba.uh.edu/chin/plsfaq/multigroup.htm
print.plspm.groups
,plot.plspm.groups
## Not run: ## example with customer satisfaction analysis ## group comparison based on the segmentation variable "gender" data(satisfaction) IMAG <- c(0,0,0,0,0,0) EXPE <- c(1,0,0,0,0,0) QUAL <- c(1,1,0,0,0,0) VAL <- c(0,1,1,0,0,0) SAT <- c(1,1,1,1,0,0) LOY <- c(1,0,0,0,1,0) sat.mat <- rbind(IMAG, EXPE, QUAL, VAL, SAT, LOY) sat.sets <- list(1:5,6:10,11:15,16:19,20:23,24:27) sat.mod <- rep("A",6) ## reflective indicators pls <- plspm(satisfaction, sat.mat, sat.sets, sat.mod, scheme="factor", scaled=FALSE) ## permutation test with 100 permutations res.group <- plspm.groups(satisfaction, pls, satisfaction$gender, method="permutation", reps=100) res.group plot(res.group) ## End(Not run)