confint.RSA | R Documentation |
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.
RSA
## 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)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.