confint.index {MLID} | R Documentation |
Confidence intervals for the multilevel index
Description
Calculates the confidence intervals for the residuals of the multilevel index at each level. These can then be visualised in a caterpillar plot.
Usage
## S3 method for class 'index'
confint(object, parm, level = 0.95, ...)
Arguments
object |
an object of class |
parm |
NA |
level |
the confidence level required |
... |
other arguments |
Details
confint.index
is a wrapper to lme4::ranef(mlm, condVar = TRUE)
and is used to calculate the confidence intervals for the locations and
regions at each of the higher levels of the model. In this way, places with
an usually high (or low) share of population group Y with respect to
population group X can be identified, net of the effects of other levels
of the model. The width of the confidence interval is adjusted for a test of
difference between two means (see Statistical Rules of Thumb by Gerald van
Belle, 2011, eq 2.18). A 95 per cent confidence interval, for example,
extends to 1.39 times the standard error around the mean and not 1.96.
Value
an object of class confint
, a list of length equal to the
number of levels in the index where each part of the list is a data frame
giving the confidence interval for the location
See Also
Examples
## Not run:
data(aggdata)
index <- id(aggdata, vars = c("Bangladeshi", "WhiteBrit"),
levels = c("MSOA","LAD","RGN"))
ci <- confint(index)
catplot(ci)
## End(Not run)