effects2 {lavaSearch2} | R Documentation |
Effects Through Pathways With Small Sample Correction
Description
Test whether a path in the latent variable model correspond to a null effect.
Similar to lava::effects
but with small sample correction (if any).
So far it only work for a single path related two variable composed of one or two edges.
Usage
effects2(object, linfct, robust, cluster, conf.level, ...)
## S3 method for class 'lvmfit'
effects2(
object,
linfct,
robust = FALSE,
cluster = NULL,
conf.level = 0.95,
to = NULL,
from = NULL,
df = lava.options()$df,
ssc = lava.options()$ssc,
...
)
## S3 method for class 'lvmfit2'
effects2(
object,
linfct,
robust = FALSE,
cluster = NULL,
conf.level = 0.95,
to = NULL,
from = NULL,
...
)
## S3 method for class 'lvmfit2'
effects(
object,
linfct,
robust = FALSE,
cluster = NULL,
conf.level = 0.95,
to = NULL,
from = NULL,
...
)
Arguments
object |
a |
linfct |
[character vector] The path for which the effect should be assessed (e.g. |
robust |
[logical] should robust standard errors be used instead of the model based standard errors? Should be |
cluster |
[integer vector] the grouping variable relative to which the observations are iid. |
conf.level |
[numeric, 0-1] level of the confidence intervals. |
... |
additional argument passed to |
from , to |
alternative to argument |
df |
[character] method used to estimate the degree of freedoms of the Wald statistic: Satterthwaite |
ssc |
[character] method used to correct the small sample bias of the variance coefficients: no correction ( |
Details
When argument object is a lvmfit
object, the method first calls estimate2
and then extract the confidence intervals.
Value
A data.frame with a row per path.