## example with customer satisfaction analysis
## group comparison based on the segmentation variable "gender"
#library(plspm)
# load dataset satisfaction
data("satisfaction")
# path matrix
IMAG = c(0,0,0,0,0,0)
EXPE = c(1,0,0,0,0,0)
QUAL = c(0,1,0,0,0,0)
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_path = rbind(IMAG, EXPE, QUAL, VAL, SAT, LOY)
# plot diagram of path matrix
innerplot(sat_path)
# blocks of outer model
sat_blocks = list(1:5, 6:10, 11:15, 16:19, 20:23, 24:27)
# vector of modes (reflective indicators)
sat_mod = rep("A", 6)
# apply plspm
satpls = plspm(satisfaction, sat_path, sat_blocks, modes = sat_mod,
scaled = FALSE)
# plot diagram of the inner model
innerplot(satpls)
# plot loadings
outerplot(satpls, what="loadings")
# plot outer weights
outerplot(satpls, what="weights")
# rescale LVs
rescores = rescale(satpls)
head(rescores)
# permutation test with 100 permutations
group_perm = plspm.groups(satpls, satisfaction$gender,
method="permutation", reps=100)
group_perm
# permutation test with 100 permutations
group_boot = plspm.groups(satpls, satisfaction$gender,
method="bootstrap", reps=100)
group_boot
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