Utility Functions For Covariance Matrices
Convenience functions to deal with covariance and correlation matrices.
getCov(x, lower = TRUE, diagonal = TRUE, sds = NULL, names = paste("V", 1:nvar, sep="")) char2num(s) cor2cov(R, sds, names = NULL)
x |
The elements of the covariance matrix. Either inside a character
string or as a numeric vector. In the former case, the function
|
lower |
Logical. If |
diagonal |
Logical. If |
sds |
A numeric vector containing the standard deviations to be
used to scale the elements in |
names |
The variable names of the observed variables. |
s |
Character string containing numeric values; comma's and semi-colons are ignored. |
R |
A correlation matrix, to be scaled into a covariance matrix. |
The getCov
function is typically used to input the lower
(or upper) triangular elements of a (symmetric) covariance matrix. In many
examples found in handbooks, only those elements are shown. However, lavaan
needs a full matrix to proceed.
The cor2cov
function is the inverse of the cov2cor
function, and scales a correlation matrix into a covariance matrix given
the standard deviations of the variables. Optionally, variable names can
be given.
# The classic Wheaton et. al. (1977) model # panel data on he stability of alienation lower <- ' 11.834, 6.947, 9.364, 6.819, 5.091, 12.532, 4.783, 5.028, 7.495, 9.986, -3.839, -3.889, -3.841, -3.625, 9.610, -21.899, -18.831, -21.748, -18.775, 35.522, 450.288 ' # convert to a full symmetric covariance matrix with names wheaton.cov <- getCov(lower, names=c("anomia67","powerless67", "anomia71", "powerless71","education","sei")) # the model wheaton.model <- ' # measurement model ses =~ education + sei alien67 =~ anomia67 + powerless67 alien71 =~ anomia71 + powerless71 # equations alien71 ~ alien67 + ses alien67 ~ ses # correlated residuals anomia67 ~~ anomia71 powerless67 ~~ powerless71 ' # fitting the model fit <- sem(wheaton.model, sample.cov=wheaton.cov, sample.nobs=932) # showing the results summary(fit, standardized=TRUE)
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