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lavaan (version 0.6-19)

modificationIndices: Modification Indices

Description

Given a fitted lavaan object, compute the modification indices (= univariate score tests) for a selected set of fixed-to-zero parameters.

Usage

modificationIndices(object, standardized = TRUE, cov.std = TRUE,
                    information = "expected",
                    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, information = "expected",
                    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)

Value

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

Arguments

object

An object of class lavaan.

standardized

If TRUE, two extra columns (sepc.lv and sepc.all) will contain standardized values for the EPCs. In the first column (sepc.lv), standardization 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.

information

character indicating the type of information matrix to use (check lavInspect for available options). "expected" information is the default, which provides better control of Type I errors.

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 selecting only those rows with operator op.

Details

Modification indices are just 1-df (or univariate) score tests. The modification index (or score test) for a single parameter reflects (approximately) the improvement in model fit (in terms of the chi-square test statistic), if we would refit the model but allow this parameter to be free. This function is a convenience function in the sense that it produces a (hopefully sensible) table of currently fixed-to-zero (or fixed to another constant) parameters. For each of these parameters, a modification index is computed, together with an expected parameter change (epc) value. It is important to realize that this function will only consider fixed-to-zero parameters. If you have equality constraints in the model, and you wish to examine what happens if you release all (or some) of these equality constraints, use the lavTestScore function.

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, minimum.value = 10, sort = TRUE)

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