confint.logis_re {pprof} | R Documentation |
Get confidence intervals for provider effects or standardized measures from a fitted logis_re
object
Description
Provide confidence intervals for provider effects or standardized measures from a random effect logistic model.
Usage
## S3 method for class 'logis_re'
confint(
object,
parm,
level = 0.95,
option = "SM",
measure = c("rate", "ratio"),
stdz = "indirect",
alternative = "two.sided",
...
)
Arguments
object |
a model fitted from |
parm |
specify a subset of providers for which confidence intervals are given.
By default, all providers are included. The class of |
level |
the confidence level. The default value is 0.95. |
option |
a character string specifying whether the confidence intervals should be provided for provider effects or standardized measures:
|
measure |
a character string or a vector indicating whether the output measure is "ratio" or "rate" if |
stdz |
a character string or a vector specifying the standardization method
if |
alternative |
a character string specifying the alternative hypothesis, must be one of
|
... |
additional arguments that can be passed to the function. |
Value
A list of data frames containing the confidence intervals based on the values of option
and stdz
.
CI.alpha |
Confidence intervals for provider effects if |
CI.indirect |
Confidence intervals for indirect standardized differences if |
CI.direct |
Confidence intervals for direct standardized differences if |
Examples
data(ExampleDataBinary)
outcome <- ExampleDataBinary$Y
ProvID <- ExampleDataBinary$ProvID
covar <- ExampleDataBinary$Z
fit_re <- logis_re(Y = outcome, Z = covar, ProvID = ProvID)
confint(fit_re)