Package: influence.ME
Type: Package
Title: Tools for detecting influential data in mixed effects models
Version: 0.9.2
Date: 2012-12-24
Author: Rense Nieuwenhuis, Ben Pelzer, Manfred te Grotenhuis
Maintainer: Rense Nieuwenhuis <r.nieuwenhuis@utwente.nl>
Description: influence.ME provides a collection of tools for
calculating measures of influential data for generalized mixed
effects models. It analyses models that were estimated using
lme4. The basic rationale behind identifying influential data
is that when iteratively single units are omitted from the
data, models based on these data should not produce
substantially different estimates. To standardize the
assessment of how influential a (single group of)
observation(s) is, several measures of influence are common
practice, such as DFBETAS and Cooks' Distance.  In addition, we
provide a measure of percentage change of the fixed point
estimates and a simple test to detect changing levels of
significance.
License: GPL-3
URL: http://www.rensenieuwenhuis.nl/r-project/influenceme/
Depends: R(>= 2.15.0), lme4, lattice
Imports: Matrix(>= 1.0)
LazyLoad: yes
LazyData: yes
Packaged: 2013-01-15 09:58:42 UTC; nieuwenhuisrr
Repository: CRAN
Date/Publication: 2013-01-15 13:48:51

practice, such as DFBETAS and Cooks' Distance. In addition, we

Title: Case Influence in Structural Equation Models
Author: Massimiliano Pastore & Gianmarco Altoe'
Description: influence.SEM provides a set of tools for evaluating several measures of case influence for Structural Equation Models following the approach of Pek and MacCallum (2011).

Description: Influence measures in Structural Equation Models: a set of tools for evaluating several measures of case influence for Structural Equation Models following the approach of Pek and MacCallum (2011).

Description: A set of tools for evaluating several measures of case influence for structural equation models. Functions are based on the approach of J Pek and RC MacCallum (Sensitivity analysis in structural equation models: cases and their influence, Multivariate Behavioral Research, 2011).