compare.res {latcontrol}

Parameter estimates of structural equation models with and without control variable(s)

Description

Comprehensive heads-on comparison of pertinent parameter estimates of two structural equation models that only differ in terms of the inclusion or exclusion of one or more control variable(s). Thereby, standardized loadings, path coefficients, and covariances as well as p-values are displayed. The models must have been fitted with the R package lavaan (Rosseel, 2012) <doi:10.18637/jss.v048.i02>. The derivation of the methodology employed in this package can be obtained from Blötner (2023) <doi:10.31234/osf.io/dy79z>.

Usage

compare.res(object_with, object_without)

Arguments

object_with

Fitted lavaan object involving the control variable(s).

object_without

Fitted lavaan object without the control variable(s).

Value

Results

A list containing the parameter estimates of the structural equation models with and without the control variable(s) outlined below.

lhs

Left-hand side of the parameter estimate both models contain.

op

Operator ('=~' indicates a loading, '~' a prediction of the left-hand side object by the right-hand side object, and '~~' an undirected covariance. See the documentation of the lavaan package (Rosseel, 2012) for details.)

rhs

Right-hand side of the parameter estimate both models contain.

label

If there are labelled parameters in the lavaan syntax, the respective labels will be echoed in the output of the compare.res() function.

est.std.with

Standardized parameter estimate in the model with the control variable(s).

p.with

p-value of the standardized parameter estimate in the model with the control variable(s).

est.std.wo

Standardized parameter estimate in the model without the control variable(s).

p.wo

p-value of the standardized parameter estimate in the model without the control variable(s).

r

Bivariate correlation between the parameter estimates detected in both models as an index of profile similarity.

Author(s)

Christian Blötner [e-mail]

References

Blötner, C. (2023). latcontrol: Evaluation of the role of control variables in structural equation models. PsyArXiv. https://doi.org/10.31234/osf.io/dy79z

Rosseel, Y. (2012). lavaan: An R package for structural equation modeling. Journal of Statistical Software, 48(2), 1–36. https://doi.org/10.18637/jss.v048.i02

Examples

data <- data.frame(i1 = rnorm(100),
                   i2 = rnorm(100),
                   i3 = rnorm(100),
                   i4 = rnorm(100),
                   i5 = rnorm(100),
                   i6 = rnorm(100),
                   i7 = rnorm(100),
                   i8 = rnorm(100),
                   i9 = rnorm(100),
                   i10 = rnorm(100),
                   i11 = rnorm(100),
                   i12 = rnorm(100))

m_with <- 'IV =~ i1 + i2 + i3 + i4
           DV =~ i5 + i6 + i7 + i8
           CV =~ i9 + i10 + i11 + i12

           DV ~ IV + CV
           IV ~ CV'
m_without <- 'IV =~ i1 + i2 + i3 + i4
              DV =~ i5 + i6 + i7 + i8

              DV ~ IV'

fit_with <- sem(m_with, data = data)
fit_without <- sem(m_without, data = data)

compare.res(fit_with, fit_without)