CFA.1 {MBESS}

One-factor confirmatory factor analysis model

Description

Returns the MLE estimates and the estimated asymptotic covariance matrix of parameter estimates for one-factor confirmatory factor analysis model

Usage

CFA.1(S, N, equal.loading = FALSE, equal.error = FALSE, package="lavaan", 
	se="standard", ...)

Arguments

S

covariance matrix of the indicators

N

total sample size

equal.loading

logical statement indicating whether the path coefficients are the same

equal.error

logical statement indicating whether the manifest variables have the same error variances

package

the package used in confirmatory factor analysis (sem or lavaan

se

See the cfa and check the se argument

...

Additional arguments for the cfa function

Value

Model

the factor analysis model specified by the user

Factor.Loadings

factor loadings

Indicator.var

the error variances of the indicator variables

Parameter.cov

the covariance matrix of the parameters

converged

TRUE or FALSE statement on if the model converged

package

notes the package used to get the output

Note

The output will differ slightly, both in form and potentially values, based on which package lavaan or sem is used.

Author(s)

Keke Lai (University of California-Merced) and Ken Kelley (University of Notre Dame)

See Also

sem, covmat.from.cfm

Examples

## Not run: 
cov.mat<- matrix(
c(1.384, 1.484, 1.988, 2.429, 3.031,
1.484, 2.756, 2.874, 3.588, 4.390,
1.988, 2.874, 4.845, 4.894, 6.080,
2.429, 3.588, 4.894, 6.951, 7.476,
3.031, 4.390, 6.080, 7.476, 10.313), nrow=5)


CFA.1(N=300, S=cov.mat, package="lavaan")

CFA.1(N=300, S=cov.mat, package="sem")


## End(Not run)