Date: Thu, 24 Mar 2011 23:45:15 -0400
Reply-To: Rich Ulrich <email@example.com>
Sender: "SPSSX(r) Discussion" <SPSSX-L@LISTSERV.UGA.EDU>
From: Rich Ulrich <firstname.lastname@example.org>
Subject: Re: outliers - casewise listing of residuals and standardized
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> Date: Sun, 20 Mar 2011 07:39:19 -0700
> From: email@example.com
> Subject: RE: outliers - casewise listing of residuals and standardized
> To: firstname.lastname@example.org; email@example.com
> Three problematic predictors:
> (1) No. of board meeting – skewness (3.4)
> (2) Firm’s asset – in dollar, skewness (17.3)
> (3) No. of subsidiary – skewness (7.7)
> N is 800. In general, the model is significant but R^2 is quite
> low(10%). I have yet to decide what to do about those extreme cases.
> Different textbooks give different suggestions.
It might be because I groom my variables before I look
at skewness, but I've usually been concerned with skewness
between 0.35 and 1.5. I'm not even convinced that it is
possible to have skewness of 17.3 or 7.7. - Would you
describe one set of those values?
"Board meetings" - In a model, I think I would be expect to see
groupings of, say, "daily/ weekly/ monthly/ annually/ less".
That grouping not going to come out very weird for skewness,
but I *might* suspect that it is non-linear and *needs*
categories, depending on the outcome variable.
"Firm's assets" - Are you trying to model across multinationals,
down to the corner grocery? Assets seems a natural for taking
a log, but it also seems natural to create a model without the
world's full range of possibilities.
"No. of subsidiaries" - This also seems like something that
deserves to put into manageable groups, either to analyze as
categories or to create a reasonable "scale" on which I might
expect a linear relation to outcome.
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