modificationIndices: Modification Indices
In nietsnel/psindex: Parameter Stability Index

Description Usage Arguments Value Examples

Modification indices of a latent variable model.

modificationIndices(object, standardized = TRUE, cov.std = 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, cov.std = 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)

`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.
`cov.std`	Logical. See `standardizedSolution`.
`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`.

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

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

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