gof function

Extract model summaries and GOF statistics for model object

Calculates various GOF statistics for model object including global chi-squared test statistic and AIC. Extract model-specific mean and variance structure, residuals and various predicitions.

gof(object, ...)

## S3 method for class 'lvmfit'
gof(object, chisq=FALSE, level=0.90, rmsea.threshold=0.05,all=FALSE,...)

moments(x,...)

## S3 method for class 'lvm'
moments(x, p, debug=FALSE, conditional=FALSE, data=NULL, latent=FALSE, ...)

## S3 method for class 'lvmfit'
logLik(object, p=coef(object),
                      data=model.frame(object),
                      model=object$estimator,
                      weights=Weights(object),
                      data2=object$data$data2,
                          ...)

## S3 method for class 'lvmfit'
score(x, data=model.frame(x), p=pars(x), model=x$estimator,
                   weights=Weights(x), data2=x$data$data2, ...)

## S3 method for class 'lvmfit'
information(x,p=pars(x),n=x$data$n,data=model.frame(x),
                   model=x$estimator,weights=Weights(x), data2=x$data$data2, ...)

Arguments

• object: Model object
• ...: Additional arguments to be passed to the low level functions
• x: Model object
• p: Parameter vector used to calculate statistics
• data: Data.frame to use
• latent: If TRUE predictions of latent variables are included in output
• data2: Optional second data.frame (only for censored observations)
• weights: Optional weight matrix
• n: Number of observations
• conditional: If TRUE the conditional moments given the covariates are calculated. Otherwise the joint moments are calculated
• model: String defining estimator, e.g. "gaussian" (see estimate)
• debug: Debugging only
• chisq: Boolean indicating whether to calculate chi-squared goodness-of-fit (always TRUE for estimator='gaussian')
• level: Level of confidence limits for RMSEA
• rmsea.threshold: Which probability to calculate, Pr(RMSEA<rmsea.treshold)
• all: Calculate all (ad hoc) FIT indices: TLI, CFI, NFI, SRMR, ...

Returns

A htest-object.

Examples

m <- lvm(list(y~v1+v2+v3+v4,c(v1,v2,v3,v4)~x))
set.seed(1)
dd <- sim(m,1000)
e <- estimate(m, dd)
gof(e,all=TRUE,rmsea.threshold=0.05,level=0.9)

set.seed(1)
m <- lvm(list(c(y1,y2,y3)~u,y1~x)); latent(m) <- ~u
regression(m,c(y2,y3)~u) <- "b"
d <- sim(m,1000)
e <- estimate(m,d)
rsq(e)
##'
rr <- rsq(e,TRUE)
rr
estimate(rr,contrast=rbind(c(1,-1,0),c(1,0,-1),c(0,1,-1)))

Author(s)

Klaus K. Holst