Learn R Programming

lavaan (version 0.5-9)

modificationIndices: Modification Indices

Description

Modification indices of a latent variable model.

Usage

modificationIndices(object, standardized = TRUE, power = FALSE, 
                    delta = 0.1, alpha = 0.05, high.power = 0.75)
modindices(object, standardized = TRUE, power = FALSE,
                    delta = 0.1, alpha = 0.05, high.power = 0.75)

Arguments

object
An object of class lavaan.
standardized
If TRUE, two extra columns (sepc.lv and sepc.all) will contain standardized values for the epc's. In the first column (sepc.lv), standardizization is based on the variances of the (continuous) latent variables. In the second column (sepc.all
power
If TRUE, the (post-hoc) power is computed for each modification index, using the values of delta and alpha.
delta
The value of the effect size, as used in the post-hoc power computation, currently using the unstandardized metric of the epc column.
alpha
The significance level used for deciding if the modification index is statistically significant or not.
high.power
If the computed power is higher than this cutoff value, the power is considered `high'. If not, the power is considered `low'. This affects the values in the 'decision' column in the output.

Value

  • A data.frame containing modification indices and EPC's.

Examples

Run this code
HS.model <- 'visual  =~ x1 + x2 + x3
              textual =~ x4 + x5 + x6
              speed   =~ x7 + x8 + x9 '

fit <- cfa(HS.model, data=HolzingerSwineford1939)
modindices(fit)

Run the code above in your browser using DataLab