lavaan (version 0.5-21)

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, sort. = FALSE, minimum.value = 0,  maximum.number = nrow(LIST), free.remove = TRUE, na.remove = TRUE, op = NULL)
modindices(object, standardized = TRUE, power = FALSE, delta = 0.1, alpha = 0.05, high.power = 0.75, sort. = FALSE, minimum.value = 0,  maximum.number = nrow(LIST), free.remove = TRUE, na.remove = TRUE, op = NULL)

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), standardization is based on both the variances of both (continuous) observed and latent variables. (Residual) covariances are standardized using (residual) variances.

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.

sort.

Logical. If TRUE, sort the output using the values of the modification index values. Higher values appear first.

minimum.value

Numeric. Filter output and only show rows with a modification index value equal or higher than this minimum value.

maximum.number

Integer. Filter output and only show the first maximum number rows. Most useful when combined with the sort. option.

free.remove

Logical. If TRUE, filter output by removing all rows corresponding to free (unconstrained) parameters in the original model.

na.remove

Logical. If TRUE, filter output by removing all rows with NA values for the modification indices.

op

Character string. Filter the output by selectin only those rows with operator op.

Value

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

Examples

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

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