findSa {Omisc} | R Documentation |
findSa
Description
This is an implementation of the YHY bootstrap covariance matrix.
Usage
findSa(S, fitted, p, a = 0.5, df, n, tau = NULL, tol = 1e-07)
Arguments
S |
Sample covariance matrix |
fitted |
The fitted covariance matrix |
p |
the number of columns in the covariance matrix |
a |
the starting value for the a parameter |
df |
the degrees of freedom in the model |
n |
the number of participants in the model |
tau |
the population tau. If no tau is provided, the estimated tau from the model will be used |
tol |
the difference between ga and tau at which the function will converge |
Value
a list of the "a" adjusted covariance matrix, Sa, the tau, ga, and the number of interations.
Examples
require(Omisc)
require(lavaan)
set.seed(2^7-1)
modelTest<-'
LV1=~ .7*x1+.8*x2+.75*x3+.6*x4
LV2=~ .7*y1+.8*y2+.75*y3+.6*y4
LV1~~.3*LV2
LV1~~1*LV1
LV2~~1*LV2
'
modelFit<-'
LV1=~ x1+x2+x3+x4
LV2=~ y1+y2+y3+y4
LV1~~start(.5)*LV2
LV1~~1*LV1
LV2~~1*LV2
'
testdata<-simulateData(modelTest, sample.nobs = 250)
fit<-cfa(modelFit, testdata)
fitted<-fitted(fit)$cov
fitted<-fitted[,1:ncol(fitted)]
S<-cov(testdata)
p<-8
a<-.5
n<-250
df<-21
findSa(S, fitted, p, .5, df, n)
[Package Omisc version 0.1.5 Index]