The central hub of the cSEM package. It acts like a
foreman by collecting all (estimation) tasks, distributing them to lower
level package functions, and eventually recollecting all of their results.
It is called by csem() to manage the actual calculations.
It may be called directly by the user, however, in most cases it will likely
be more convenient to use csem() instead.
foreman(
.data = args_default()$.data,
.model = args_default()$.model,
.approach_cor_robust = args_default()$.approach_cor_robust,
.approach_nl = args_default()$.approach_nl,
.approach_paths = args_default()$.approach_paths,
.approach_weights = args_default()$.approach_weights,
.conv_criterion = args_default()$.conv_criterion,
.disattenuate = args_default()$.disattenuate,
.dominant_indicators = args_default()$.dominant_indicators,
.estimate_structural = args_default()$.estimate_structural,
.id = args_default()$.id,
.instruments = args_default()$.instruments,
.iter_max = args_default()$.iter_max,
.normality = args_default()$.normality,
.PLS_approach_cf = args_default()$.PLS_approach_cf,
.PLS_ignore_structural_model = args_default()$.PLS_ignore_structural_model,
.PLS_modes = args_default()$.PLS_modes,
.PLS_weight_scheme_inner = args_default()$.PLS_weight_scheme_inner,
.reliabilities = args_default()$.reliabilities,
.starting_values = args_default()$.starting_values,
.tolerance = args_default()$.tolerance
)A data.frame or a matrix 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.
A model in lavaan model syntax or a cSEMModel list.
Character string. Approach used to obtain a robust
indicator correlation matrix. One of: "none" in which case the standard
Bravais-Pearson correlation is used,
"spearman" for the Spearman rank correlation, or
"mcd" via MASS::cov.rob() for a robust correlation matrix.
Defaults to "none". Note that many postestimation procedures (such as
testOMF() or fit() implicitly assume a continuous
indicator correlation matrix (e.g. Bravais-Pearson correlation matrix).
Only use if you know what you are doing.
Character string. Approach used to estimate nonlinear structural relationships. One of: "sequential" or "replace". Defaults to "sequential".
Character string. Approach used to estimate the
structural coefficients. One of: "OLS" or "2SLS". If "2SLS", instruments
need to be supplied to .instruments. Defaults to "OLS".
Character string. Approach used to obtain composite weights. One of: "PLS-PM", "SUMCORR", "MAXVAR", "SSQCORR", "MINVAR", "GENVAR", "GSCA", "PCA", "unit", "bartlett", or "regression". Defaults to "PLS-PM".
Character string. The criterion to use for the convergence check. One of: "diff_absolute", "diff_squared", or "diff_relative". Defaults to "diff_absolute".
Logical. Should composite/proxy correlations
be disattenuated to yield consistent loadings and path estimates if at least
one of the construct is modeled as a common factor? Defaults to TRUE.
A character vector of "construct_name" = "indicator_name" pairs,
where "indicator_name" is a character string giving the name of the dominant indicator
and "construct_name" a character string of the corresponding construct name.
Dominant indicators may be specified for a subset of the constructs.
Default to NULL.
Logical. Should the structural coefficients
be estimated? Defaults to TRUE.
Character string or integer. A character string giving the name or
an integer of the position of the column of .data whose levels are used
to split .data into groups. Defaults to NULL.
A named list of vectors of instruments. The names
of the list elements are the names of the dependent (LHS) constructs of the structural
equation whose explanatory variables are endogenous. The vectors
contain the names of the instruments corresponding to each equation. Note
that exogenous variables of a given equation must be supplied as
instruments for themselves. Defaults to NULL.
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 to 100.
Logical. Should joint normality of
\([\eta_{1:p}; \zeta; \epsilon]\)
be assumed in the nonlinear model? See Dijkstra2014cSEM for details.
Defaults to FALSE. Ignored if the model is not nonlinear.
Character string. Approach used to obtain the correction
factors for PLSc. One of: "dist_squared_euclid", "dist_euclid_weighted",
"fisher_transformed", "mean_arithmetic", "mean_geometric", "mean_harmonic",
"geo_of_harmonic". Defaults to "dist_squared_euclid".
Ignored if .disattenuate = FALSE or if .approach_weights is not PLS-PM.
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.
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, or NULL.
Possible choices for mode 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 to NULL.
If NULL the appropriate mode according to the type
of construct used is chosen. Ignored if .approach_weight is not PLS-PM.
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.
A character vector of "name" = value pairs,
where value is a number between 0 and 1 and "name" a character string
of the corresponding construct name, or NULL. Reliabilities
may be given for a subset of the constructs. Defaults to NULL in which case
reliabilities are estimated by csem(). Currently, only supported for
.approach_weights = "PLS-PM".
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, where value is the (scaled or unscaled) starting weight. Defaults to NULL.
Double. The tolerance criterion for convergence.
Defaults to 1e-05.
csem, cSEMResults