Calculate composite weights using the partial least squares path modeling (PLS-PM) algorithm Wold1975cSEM.
Usage
calculateWeightsPLS(
.data = args_default()$.data,
.S = args_default()$.S,
.csem_model = args_default()$.csem_model,
.conv_criterion = args_default()$.conv_criterion,
.iter_max = args_default()$.iter_max,
.PLS_ignore_structural_model = args_default()$.PLS_ignore_structural_model,
.PLS_modes = args_default()$.PLS_modes,
.PLS_weight_scheme_inner = args_default()$.PLS_weight_scheme_inner,
.starting_values = args_default()$.starting_values,
.tolerance = args_default()$.tolerance
)
Arguments
- .data
A
data.frame
or amatrix
of standardized or unstandardized data (indicators/items/manifest variables). Possible column types or classes of the data provided are: "logical
", "numeric
" ("double
" or "integer
"), "factor
" ("ordered
" and/or "unordered
"), "character
" (converted to factor), or a mix of several types.- .S
The (K x K) empirical indicator correlation matrix.
- .csem_model
A (possibly incomplete) cSEMModel-list.
- .conv_criterion
Character string. The criterion to use for the convergence check. One of: "diff_absolute", "diff_squared", or "diff_relative". Defaults to "diff_absolute".
- .iter_max
Integer. The maximum number of iterations allowed. If
iter_max = 1
and.approach_weights = "PLS-PM"
one-step weights are returned. If the algorithm exceeds the specified number, weights of iteration step.iter_max - 1
will be returned with a warning. Defaults to100
.- .PLS_ignore_structural_model
Logical. Should the structural model be ignored when calculating the inner weights of the PLS-PM algorithm? Defaults to
FALSE
. Ignored if.approach_weights
is not PLS-PM.- .PLS_modes
Either a named list specifying the mode that should be used for each construct in the form
"construct_name" = mode
, a single character string giving the mode that should be used for all constructs, orNULL
. Possible choices formode
are: "modeA", "modeB", "modeBNNLS", "unit", "PCA", a single integer or a vector of fixed weights of the same length as there are indicators for the construct given by"construct_name"
. If only a single number is provided this is identical to using unit weights, as weights are rescaled such that the related composite has unit variance. Defaults toNULL
. IfNULL
the appropriate mode according to the type of construct used is chosen. Ignored if.approach_weight
is not PLS-PM.- .PLS_weight_scheme_inner
Character string. The inner weighting scheme used by PLS-PM. One of: "centroid", "factorial", or "path". Defaults to "path". Ignored if
.approach_weight
is not PLS-PM.- .starting_values
A named list of vectors where the list names are the construct names whose indicator weights the user wishes to set. The vectors must be named vectors of
"indicator_name" = value
pairs, wherevalue
is the (scaled or unscaled) starting weight. Defaults toNULL
.- .tolerance
Double. The tolerance criterion for convergence. Defaults to
1e-05
.
Value
A named list. J stands for the number of constructs and K for the number of indicators.
$W
A (J x K) matrix of estimated weights.
$E
A (J x J) matrix of inner weights.
$Modes
A named vector of modes used for the outer estimation.
$Conv_status
The convergence status.
TRUE
if the algorithm has converged andFALSE
otherwise. If one-step weights are used via.iter_max = 1
or a non-iterative procedure was used, the convergence status is set toNULL
.$Iterations
The number of iterations required.