chandwich-package {chandwich} | R Documentation |
chandwich: Chandler-Bate Sandwich Loglikelihood Adjustment
Description
Performs adjustments of an independence loglikelihood using a robust sandwich estimator of the parameter covariance matrix, based on the methodology in Chandler and Bate (2007). This can be used for cluster correlated data when interest lies in the parameters of the marginal distributions. Functions for profiling the adjusted loglikelihoods are also provided, as are functions for calculating and plotting confidence intervals, for single model parameters, and confidence regions, for pairs of model parameters.
Details
The main function in the chandwich package is adjust_loglik
. It
finds the maximum likelihood estimate (MLE) of model parameters based on
an independence loglikelihood in which cluster dependence in the data is
ignored. The independence loglikelihood is adjusted in a way that ensures
that the Hessian of the adjusted loglikelihood coincides with a robust
sandwich estimate of the parameter covariance at the MLE. Three
adjustments are available: one in which the independence loglikelihood
itself is scaled (vertical scaling) and two others where the scaling
is in the parameter vector (horizontal scaling).
See Chandler and Bate (2007) for full details and
vignette("chandwich-vignette", package = "chandwich")
for an
overview of the package.
Author(s)
Maintainer: Paul J. Northrop p.northrop@ucl.ac.uk [copyright holder]
Authors:
Richard E. Chandler [copyright holder]
References
Chandler, R. E. and Bate, S. (2007). Inference for clustered data using the independence loglikelihood. Biometrika, 94(1), 167-183. doi:10.1093/biomet/asm015
See Also
adjust_loglik
to adjust a user-supplied
loglikelihood.
compare_models
to compare nested models using an
adjusted loglikelihood ratio test. See also the S3 method
anova.chandwich
.
conf_intervals
to calculate confidence intervals
for individual model parameters. See also the S3 method
confint.chandwich
.
conf_region
to calculate a confidence region
for a pair of model parameters.