sam: Fit Structural Equation Models using the SAM approach

In lavaan: Latent Variable Analysis

Description

Fit a Structural Equation Model (SEM) using the Structural After Measurement (SAM) approach.

Usage

sam(model = NULL, data = NULL, cmd = "sem",
    mm.list = NULL, mm.args = list(bounds = "standard"), 
    struc.args = list(fixed.x = FALSE),
    sam.method = "local", ...,
    local.options = list(M.method = "ML", veta.force.pd = TRUE,
                         twolevel.method = "h1"),
    global.options = list(),
    output = "lavaan")

Arguments

model	A description of the user-specified model. Typically, the model is described using the lavaan model syntax. See model.syntax for more information. Alternatively, a parameter table (eg. the output of the lavaanify() function) is also accepted.
data	A data frame containing the observed variables used in the model.
cmd	Character. Which command is used to run the sem models. The possible choices are "sem", "cfa" or "lavaan", determining how we deal with default options.
mm.list	List. Define the measurement blocks. Each element of the list should be either a single name of a latent variable, or a vector of latent variable names. If omitted, a separate measurement block is used for each latent variable.
mm.args	List. Optional arguments for the fitting function(s) of the measurement block(s) only. See lavOptions for a complete list.
struc.args	List. Optional arguments for the fitting function of the structural part only. See lavOptions for a complete list.
sam.method	Character. Can be set to "local" or "global".
...	Many more additional options can be defined, using 'name = value'. See lavOptions for a complete list. These options affect both the measurement blocks and the structural part.
local.options	List. Options specific for local SAM method (these options may change over time).
global.options	List. Options specific for global SAM method (not used for now).
output	Character. If "lavaan", a lavaan object returned. If "list", a list is returned with all the ingredients from the different stages.

Details

The sam function tries to automate the SAM approach, by first estimating the measurement part of the model, and then the structural part of the model. See reference for more details.

Value

If output = "lavaan", an object of class lavaan, for which several methods are available, including a summary method. If output = "list", a list.

References

Rosseel and Loh (2021). A structural-after-measurement (SAM) approach to SEM. URL https://osf.io/pekbm/.

See Also

lavaan

Examples

## The industrialization and Political Democracy Example 
## Bollen (1989), page 332
model <- ' 
  # latent variable definitions
     ind60 =~ x1 + x2 + x3
     dem60 =~ y1 + a*y2 + b*y3 + c*y4
     dem65 =~ y5 + a*y6 + b*y7 + c*y8

  # regressions
    dem60 ~ ind60
    dem65 ~ ind60 + dem60

  # residual correlations
    y1 ~~ y5
    y2 ~~ y4 + y6
    y3 ~~ y7
    y4 ~~ y8
    y6 ~~ y8
'

fit.sam <- sam(model, data = PoliticalDemocracy,
               mm.list = list(ind = "ind60", dem = c("dem60", "dem65")))
summary(fit.sam)

lavaan documentation built on June 27, 2021, 5:07 p.m.