rescale | R Documentation |
Rescale standardized latent variable scores to original scale of manifest variables
rescale(pls, data = NULL)
pls |
object of class |
data |
Optional dataset (matrix or data frame) used
when argument |
rescale
requires all outer weights to be positive
A data frame with the rescaled latent variable scores
Gaston Sanchez
plspm
## Not run: ## example with customer satisfaction analysis # load data satisfaction data(satisfaction) # define inner model 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) # define outer model list sat_blocks = list(1:5, 6:10, 11:15, 16:19, 20:23, 24:27) # define vector of reflective modes sat_modes = rep("A", 6) # apply plspm my_pls = plspm(satisfaction, sat_path, sat_blocks, modes = sat_modes, scaled=FALSE) # rescaling standardized scores of latent variables new_scores = rescale(my_pls) # compare standardized LVs against rescaled LVs summary(my_pls$scores) summary(new_scores) ## End(Not run)
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