modsem_pi: Interaction between latent variables using product indicators

In modsem: Latent Interaction (and Moderation) Analysis in Structural Equation Models (SEM)

Interaction between latent variables using product indicators

Description

modsem_pi() is a function for estimating interaction effects between latent variables, in structural equation models (SEMs), using product indicators. Methods for estimating interaction effects in SEMs can basically be split into two frameworks: 1. Product Indicator based approaches ("dblcent", "rca", "uca", "ca", "pind"), and 2. Distributionally based approaches ("lms", "qml"). modsem_pi() is essentially a fancy wrapper for lavaan::sem() which generates the necessary syntax and variables for the estimation of models with latent product indicators. Use default_settings_pi() to get the default settings for the different methods.

Usage

modsem_pi(
  model.syntax = NULL,
  data = NULL,
  method = "dblcent",
  match = NULL,
  standardize.data = FALSE,
  center.data = FALSE,
  first.loading.fixed = TRUE,
  center.before = NULL,
  center.after = NULL,
  residuals.prods = NULL,
  residual.cov.syntax = NULL,
  constrained.prod.mean = NULL,
  constrained.loadings = NULL,
  constrained.var = NULL,
  constrained.res.cov.method = NULL,
  auto.scale = "none",
  auto.center = "none",
  estimator = "ML",
  group = NULL,
  run = TRUE,
  na.rm = FALSE,
  suppress.warnings.lavaan = FALSE,
  suppress.warnings.match = FALSE,
  ...
)

Arguments

model.syntax	lavaan syntax
data	dataframe
method	method to use: "rca" = residual centering approach (passed to lavaan), "uca" = unconstrained approach (passed to lavaan), "dblcent" = double centering approach (passed to lavaan), "pind" = prod ind approach, with no constraints or centering (passed to lavaan), "custom" = use parameters specified in the function call (passed to lavaan)
match	should the product indicators be created by using the match-strategy
standardize.data	should data be scaled before fitting model
center.data	should data be centered before fitting model
first.loading.fixed	Should the first factor loading in the latent product be fixed to one?
center.before	should indicators in products be centered before computing products (overwritten by method, if method != NULL)
center.after	should indicator products be centered after they have been computed?
residuals.prods	should indicator products be centered using residuals (overwritten by method, if method != NULL)
residual.cov.syntax	should syntax for residual covariances be produced (overwritten by method, if method != NULL)
constrained.prod.mean	should syntax for product mean be produced (overwritten by method, if method != NULL)
constrained.loadings	should syntax for constrained loadings be produced (overwritten by method, if method != NULL)
constrained.var	should syntax for constrained variances be produced (overwritten by method, if method != NULL)
constrained.res.cov.method	method for constraining residual covariances
auto.scale	methods which should be scaled automatically (usually not useful)
auto.center	methods which should be centered automatically (usually not useful)
estimator	estimator to use in lavaan
group	group variable for multigroup analysis
run	should the model be run via lavaan, if FALSE only modified syntax and data is returned
na.rm	should missing values be removed (case-wise)? Defaults to FALSE. If TRUE, missing values are removed case-wise. If FALSE they are not removed.
suppress.warnings.lavaan	should warnings from lavaan be suppressed?
suppress.warnings.match	should warnings from match be suppressed?
...	arguments passed to other functions, e.g., lavaan

Value

modsem object

Examples

library(modsem)
# For more examples, check README and/or GitHub.
# One interaction
m1 <- '
  # Outer Model
  X =~ x1 + x2 +x3
  Y =~ y1 + y2 + y3
  Z =~ z1 + z2 + z3

  # Inner model
  Y ~ X + Z + X:Z
'

# Double centering approach
est1 <- modsem_pi(m1, oneInt)
summary(est1)

## Not run: 
# The Constrained Approach
est1Constrained <- modsem_pi(m1, oneInt, method = "ca")
summary(est1Constrained)

## End(Not run)

# Theory Of Planned Behavior
tpb <- '
# Outer Model (Based on Hagger et al., 2007)
  ATT =~ att1 + att2 + att3 + att4 + att5
  SN =~ sn1 + sn2
  PBC =~ pbc1 + pbc2 + pbc3
  INT =~ int1 + int2 + int3
  BEH =~ b1 + b2

# Inner Model (Based on Steinmetz et al., 2011)
  # Covariances
  ATT ~~ SN + PBC
  PBC ~~ SN
  # Causal Relationships
  INT ~ ATT + SN + PBC
  BEH ~ INT + PBC
  BEH ~ INT:PBC
'

# Double centering approach
estTpb <- modsem_pi(tpb, data = TPB)
summary(estTpb)

## Not run: 
# The Constrained Approach
estTpbConstrained <- modsem_pi(tpb, data = TPB, method = "ca")
summary(estTpbConstrained)

## End(Not run)

modsem documentation built on April 3, 2025, 7:51 p.m.