parameterEstimates {lavaan}R Documentation

Parameter Estimates

Description

Parameter estimates of a latent variable model.

Usage

parameterEstimates(object, ci = TRUE, level = 0.95, 
                   boot.ci.type = "perc", standardized = FALSE,
                   fmi = "default", remove.eq = TRUE, 
                   remove.ineq = TRUE, remove.def = FALSE)

Arguments

object

An object of class lavaan.

ci

If TRUE, confidence intervals are added to the output

level

The confidence level required.

boot.ci.type

If bootstrapping was used, the type of interval required. The value should be one of "norm", "basic", "perc", or "bca.simple". For the first three options, see the help page of the boot.ci function in the boot package. The "bca.simple" option produces intervals using the adjusted bootstrap percentile (BCa) method, but with no correction for acceleration (only for bias).

standardized

If TRUE, standardized estimates are added to the output

fmi

Logical. If TRUE, an extra column is added containing the fraction of missing information for each estimated parameter. If "default", the value is set to TRUE only if estimator="ML", missing="(fi)ml", and se="standard". See references for more information.

remove.eq

Logical. If TRUE, filter the output by removing all rows containing equality constraints, if any.

remove.ineq

Logical. If TRUE, filter the output by removing all rows containing inequality constraints, if any.

remove.def

Logical. If TRUE, filter the ouitput by removing all rows containing parameter definitions, if any.

Value

A data.frame containing the estimated parameters, parameters, standard errors, z-values, and (by default) the lower and upper values of the confidence intervals. If requested, extra columns are added with standardized versions of the parameter estimates.

References

Savalei, V. & Rhemtulla, M. (2012). On obtaining estimates of the fraction of missing information from FIML. Structural Equation Modeling: A Multidisciplinary Journal, 19(3), 477-494.

Examples

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

fit <- cfa(HS.model, data=HolzingerSwineford1939)
parameterEstimates(fit)
[Package lavaan version 0.5-18 Index]