Date:         Thu, 24 Mar 2011 23:45:15 -0400
Reply-To:     Rich Ulrich <rich-ulrich@live.com>
Sender:       "SPSSX(r) Discussion" <SPSSX-L@LISTSERV.UGA.EDU>
From:         Rich Ulrich <rich-ulrich@live.com>
Subject:      Re: outliers - casewise listing of residuals and standardized
              residuals
Comments: To: chuiling23@yahoo.com
In-Reply-To:  <582653.41927.qm@web120515.mail.ne1.yahoo.com>
Content-Type: text/plain; charset="Windows-1252"

> Date: Sun, 20 Mar 2011 07:39:19 -0700
> From: chuiling23@yahoo.com
> Subject: RE: outliers - casewise listing of residuals and standardized
> residuals
> To: spssx-l@listserv.uga.edu; rich-ulrich@live.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.

--
Rich Ulrich






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