Computes confidence intervals for RSA parameters, standard or bootstrapped
Computes confidence intervals for RSA parameters, standard or bootstrapped (using a percentile bootstrap)
## S3 method for class 'RSA' confint( object, parm, level = 0.95, ..., model = "full", digits = 3, method = "standard", R = 5000 )
object |
An RSA object |
parm |
Not used. |
level |
The confidence level required. |
... |
Additional parameters passed to the bootstrapLavaan function, e.g., |
model |
A string specifying the model; defaults to "full" |
digits |
Number of digits the output is rounded to; if NA, digits are unconstrained |
method |
"standard" returns the CI for the lavaan object as it was computed. "boot" computes new percentile bootstrapped CIs. |
R |
If |
There are two ways of getting bootstrapped CIs and p-values in the RSA package If you use the option se="boot" in the RSA function, lavaan provides CIs and p-values based on the bootstrapped standard error (not percentile bootstraps). If you use confint(..., method="boot"), in contrast, you get CIs and p-values based on percentile bootstrap.
## Not run:
set.seed(0xBEEF)
n <- 300
err <- 2
x <- rnorm(n, 0, 5)
y <- rnorm(n, 0, 5)
df <- data.frame(x, y)
df <- within(df, {
diff <- x-y
absdiff <- abs(x-y)
SD <- (x-y)^2
z.sq <- SD + rnorm(n, 0, err)
})
r1 <- RSA(z.sq~x*y, df, models="SSQD")
(c1 <- confint(r1, model="SSQD"))
# Dummy example with 10 bootstrap replications - better use >= 5000!
(c2 <- confint(r1, model="SSQD", method="boot", R=10))
# multicore version
confint(r1, model="SSQD", R=5000, parallel="multicore", ncpus=2)
## End(Not run)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.