cfa
constcfa: (syntax,spec) =>object=sem
Defined in: index.js:112
Alias: confirmatory factor analysis (same engine, reads better in code).
Fit a structural equation model.
Parameters
syntax
string
lavaan-style model syntax:
factor =~ ind1 + ind2 (measurement), y ~ x1 + x2 (regression),
a ~~ b ((co)variance), 1*x (fix), NA*x (free a default-fixed
parameter)
spec?
cov?
number[][]
Sample covariance (instead of
data), maximum-likelihood (divisor-N) scaling, matching what sampleCov
produces and the returned S. If you hold an unbiased (divisor-(N-1))
covariance — R’s cov(), most stats packages — rescale it by (n-1)/n
first so the chi-square, log-likelihood, AIC and BIC match lavaan.
data?
any[]
Rows as objects (column per variable)
n?
number
Sample size (required with cov)
names?
string[]
Variable names (required with cov)
Returns
object
Fitted model: parameter estimates, fit measures, model-implied Sigma,
reordered sample covariance S, and a summary() text formatter
converged
converged:
boolean
estimates
estimates:
object[]
fit
fit:
object
fit.aic
aic:
number
fit.baselineChisq
baselineChisq:
number
fit.baselineDf
baselineDf:
number
fit.bic
bic:
number
fit.cfi
cfi:
number
fit.chisq
chisq:
number
fit.df
df:
number
fit.fmin
fmin:
number
fit.logLik
logLik:
number
fit.n
n:
number
fit.npar
npar:
number
fit.pvalue
pvalue:
number
fit.rmsea
rmsea:
number
fit.srmr
srmr:
number
fit.tli
tli:
number
iterations
iterations:
number
latents
latents:
string[]
observed
observed:
string[]
S
S:
number[][]
Sigma
Sigma:
number[][]
summary
summary: () =>
string
Returns
string
theta
theta:
number[]
variables
variables:
string[]