A while back I asked about getting a list of points that R considers influential
after fitting a linear model, and very quickly got a helpful pointer to
influence.measures(). But "it has happened again." The trouble I am
having is that points marked on plots are not flagged in the output from
influence.measures(), and I can't read them on the plots. I tried some
successive deletion, but then other points (naturally) start to look
troublesome).
Is there a good way to get a list of suspicious entries at the beginning? In
this case, I am trying to help identify possible data entry errors, and I am
interested in knowing what R bothered to mark up front. Perhaps the defaults
should be telling me that what I want to do is silly, but it sure _seems_ like
it would be helpful. Is there a way to control the threshold used by
influence.measures() to get it to flag more items at one time? I am learning
the hard way, so feel free to tell me that I should be trying to do this some
other way.
Bill
