influence.measures gives several measures of influence for each  
observation (Cook's Distance, etc) and actually flags observations  
that it determines are influential by any of the measures. Looks  
good! But how does it discriminate between the influential and non- 
influential observations by each of the measures? Like does it do a  
Bonferroni-corrected t on the residuals identified by the influence  
measures or some other test?

Cheers,

Frank Tamborello, PhD
W. M. Keck Postdoctoral Fellow
School of Health Information Sciences
University of Texas Health Science Center, Houston


	[[alternative HTML version deleted]]

