matrixpls (version 0.4.0)

params.tsls: Parameter estimation with two-stage least squares

Description

Estimates the model parameters with weighted composites using two-stage least squares

Usage

params.tsls(S, model, W, ...)

Arguments

S

Covariance matrix of the data.

model

There are two options for this argument: 1. lavaan script or lavaan parameter table, or 2. a list containing three matrices inner, reflective, and formative defining the free regression paths in the model.

W

Weight matrix, where the indicators are on colums and composites are on the rows.

...

All other arguments are passed through to weightFunction and parameterEstimator.

Value

• A named vector of parameter estimates.

Details

params.tsls estimates the statistical model described by model with the following steps. If model is not in the native format, it is converted to the native format containing matrices inner, reflective, and formative. The weights W and the data covariance matrix S are used to calculate the composite covariance matrix C and the indicator-composite covariance matrix IC. These are used to estimate multiple regression models with two-stage least squares for inner model and OLS regressions for the outer model.

See Also

Other parameter estimators: params.plsc; params.plsregression; params.regression