Unstandardized Parameter Estimates

Transform parameter estimates from a fitted PLS-SEM model to observed- and latent-variable scales. Variables not selected through unstandardized remain on their standardized scales.

plsUnstandardizedEstimates(
  model,
  unstandardized = "all",
  se = c("delta", "none"),
  scale.uncertainty = FALSE,
  eps = 1e-04,
  zero.tol = 1e-10,
  rm.tmp.ov = TRUE,
  clean.tmp.ind = TRUE
)

Arguments

model

A fitted PlsModel object.

unstandardized

Character vector naming variables to unstandardize, or one of "all", "ov", or "lv".

se

Character string selecting delta-method standard errors ("delta") or no standard errors ("none").

scale.uncertainty

Should scale uncertainty be included? defaults to FALSE.

eps

Positive numeric finite-difference step used for the delta-method Jacobian.

zero.tol

Non-negative numeric tolerance below which standard errors are returned as missing.

rm.tmp.ov

Logical; whether rows involving temporary observed variables should be removed from the returned parameter table.

clean.tmp.ind

Logical; whether rows involving temporary indicators should be cleaned from the returned parameter table.

Value

A PlsSemParTable containing transformed estimates and (when requested) delta-method standard errors. The transformed covariance matrix is stored in the "vcov" attribute.

Examples

if (FALSE) { # \dontrun{
tpb <- '
# Outer Model (Based on Hagger et al., 2007)
  ATT <~ att1 + att2 + att3 + att4 + att5
  SN =~ sn1 + sn2
  PBC =~ pbc1 + pbc2 + pbc3
  INT =~ int1 + int2 + int3
  BEH <~ b1 + b2

# Inner Model (Based on Steinmetz et al., 2011)
  INT ~ ATT + SN + PBC
  BEH ~ INT + PBC + INT:PBC
'

fit <- pls(tpb, modsem::TPB, bootstrap = TRUE, boot.R = 50)
unstandardized_estimates(fit)
} # }