lavaan (version 0.6-17)

fitMeasures: Fit Measures for a Latent Variable Model

Description

This function computes a variety of fit measures to assess the global fit of a latent variable model.

Usage

fitMeasures(object, fit.measures = "all", baseline.model = NULL, 
            fm.args = list(standard.test     = "default",
                           scaled.test       = "default",
                           rmsea.ci.level    = 0.90,
                           rmsea.close.h0    = 0.05,
                           rmsea.notclose.h0 = 0.08,
                           robust            = TRUE,
                           cat.check.pd      = TRUE),
            output = "vector", ...)
fitmeasures(object, fit.measures = "all", baseline.model = NULL, 
            fm.args = list(standard.test     = "default",
                           scaled.test       = "default",
                           rmsea.ci.level    = 0.90,
                           rmsea.close.h0    = 0.05,
                           rmsea.notclose.h0 = 0.08,
                           robust            = TRUE,
                           cat.check.pd      = TRUE),
            output = "vector", ...)

Value

A named numeric vector of fit measures.

Arguments

object

An object of class lavaan.

fit.measures

If "all", all fit measures available will be returned. If only a single or a few fit measures are specified by name, only those are computed and returned.

baseline.model

If not NULL, an object of class lavaan, representing a user-specified baseline model. If a baseline model is provided, all fit indices relying on a baseline model (eg. CFI or TLI) will use the test statistics from this user-specified baseline model, instead of the default baseline model.

fm.args

List. Additional options for certain fit measures. The standard.test element determines the main test statistic (chi-square value) that will be used to compute all the fit measures that depend on this test statistic. Usually this is "standard". The scaled.test element determines which scaling method is to be used for the scaled fit measures (in case multiple scaling methods were requested). The rmsea.ci.level element determines the level of the confidence interval for the rmsea value. The rmsea.close.h0 element is the rmsea value that is used under the null hypothesis that rmsea <= rmsea.close.h0. The rmsea.notclose.h0 element is the rmsea value that is used under the null hypothesis that rsmsea >= rmsea.notclose.h0. The robust element can be set to FALSE to avoid computing the so-called robust rmsea/cfi measures (for example if the computations take too long). The cat.check.pd element is only used when data is categorical. If TRUE, robust values for RMSEA and CFI are only computed if the input correlation matrix is positive-definite (for all groups).

output

Character. If "vector" (the default), display the output as a named (lavaan-formatted) vector. If "matrix", display the output as a 1-column matrix. If "text", display the output using subsections and verbose descriptions. The latter is used in the summary output, and does not print the chi-square test by default. In addition, fit.measures should contain the main ingredient (for example "rmsea") if related fit measures are requested (for example "rmsea.ci.lower"). Otherwise, nothing will be printed in that section. See the examples how to add the chi-square test in the text output.

...

Further arguments passed to or from other methods. Not currently used for lavaan objects.

Examples

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

fit <- cfa(HS.model, data=HolzingerSwineford1939)
fitMeasures(fit)
fitMeasures(fit, "cfi")
fitMeasures(fit, c("chisq", "df", "pvalue", "cfi", "rmsea"))
fitMeasures(fit, c("chisq", "df", "pvalue", "cfi", "rmsea"), 
            output = "matrix")
print(fitMeasures(fit, c("chisq", "df", "pvalue", "cfi", "rmsea"),
                  output = "text"), add.h0 = TRUE)