Estimates the coefficients of the structural model (nonlinear and linear) using OLS, 2SLS. The latter currently work for linear models only.

estimatePath(
.approach_nl      = args_default()$.approach_nl, .approach_paths = args_default()$.approach_paths,
.csem_model       = args_default()$.csem_model, .H = args_default()$.H,
.normality        = args_default()$.normality, .P = args_default()$.P,
.Q                = args_default()\$.Q
)

## Arguments

.approach_nl

Character string. Approach used to estimate nonlinear structural relationships. One of: "sequential" or "replace". Defaults to "sequential".

.approach_paths

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".

.csem_model

A (possibly incomplete) cSEMModel-list.

.H

The (N x J) matrix of construct scores.

.normality

Logical. Should joint normality of $$[\eta_{1:p}; \zeta; \epsilon]$$ be assumed in the nonlinear model? See (Dijkstra and Schermelleh-Engel 2014) for details. Defaults to FALSE. Ignored if the model is not nonlinear.

.P

A (J x J) construct variance-covariance matrix (possibly disattenuated).

.Q

A vector of composite-construct correlations with element names equal to the names of the J construct names used in the measurement model. Note Q^2 is also called the reliability coefficient.

## Value

A named list containing the estimated structural coefficients, the R2, the adjusted R2, and the VIF's for each regression.