summary.norm {norm2}R Documentation

Summarize information from EM or MCMC algorithms

Description

Method for summarizing the results from a call to the functions emNorm or mcmcNorm.

Usage

## S3 method for class 'norm'
summary(object, show.variables = (object$method == "EM"),
   show.patterns = (object$method == "EM"),
   show.params = (object$method =="EM"), ...) 

## S3 method for class 'summary.norm'
print(x, ...)

Arguments

object

an object of class "norm" which is produced as the result of a call to emNorm or mcmcNorm; see DETAILS below.

show.variables

if TRUE, then tables summarizing the response variables and covariates used in the model will be printed.

show.patterns

if TRUE, then a table summarizing the patterns of missingness will be printed.

show.params

if TRUE, then the final values of the parameters (estimates after the final iteration of EM or simulated values after the final iteration of MCMC) will be printed.

x

a result from summary.norm.

...

values to be passed to the methods.

Details

The result from a call to emNorm or mcmcNorm is an object of class "norm", which is a list containing results from the EM or MCMC run. The function summary.norm, which is invoked through the generic method summary, summarizes the information contained in this object.

The result from summary.norm is an object of class "summary.norm" which can be displayed or printed via the generic method print.

Value

A list that includes all the original components of obj plus some additional summaries that are printed via a call to the generic method print. These include:

x.table

a summary of all variables appearing in the model as predictors or covariates.

y.table

a summary of all variables appearing in the model as responses or outcomes.

em.summary

a summary of the results from the EM run, including: the number of iterations; whether EM converged; and an empirical estimate of the rate of convergence which estimates the worst fraction of missing information.

mcmc.summary

a summary of the results from the MCMC run, including: the number of iterations; whether imputations were created and, if so, how many; and whether parameter series were saved.

Author(s)

Joe Schafer Joseph.L.Schafer@census.gov

References

For more information about this function and other functions in the norm2 package, see User's Guide for norm2 in the library subdirectory doc.

See Also

emNorm, mcmcNorm

Examples

## run EM for cholesterol data and summarize
data(cholesterol)
emResult <- emNorm(cholesterol)
summary(emResult)

## run MCMC starting from the ML estimates and summarize
mcmcResult <- mcmcNorm(emResult)
summary(mcmcResult)

[Package norm2 version 2.0.2 Index]