| summary.mcml {glmmrBase} | R Documentation |
Summarises an mcml fit output
Description
Summary method for class "'mcml'"
Usage
## S3 method for class 'mcml'
summary(object, ...)
Arguments
object |
an object of class "'mcml'" as a result of a call to MCML, see Model |
... |
Further arguments passed from other methods |
Details
'print.mcml' tries to replicate the output of other regression functions, such as 'lm' and 'lmer' reporting parameters, standard errors, and z- and p- statistics. The z- and p- statistics should be interpreted cautiously however, as generalised linear miobjected models can suffer from severe small sample biases where the effective sample size relates more to the higher levels of clustering than individual observations.
Parameters 'b' are the mean function beta parameters, parameters 'cov' are the covariance function parameters in the same order as '$covariance$parameters', and parameters 'd' are the estimated random effects.
Value
A list with random effect names and a data frame with random effect mean and credible intervals