Re: [R] [Not R question]: Better fit for order probit model

From: Robert A LaBudde <ral_at_lcfltd.com>
Date: Sun, 17 Jun 2007 16:12:43 -0400

At 01:29 PM 6/17/2007, adschai wrote:
>Thank you so much Robert. Please find the information below.
>
>The scale 1-10 are subjective physical condition ratings scored by
>inspection engineers at the site. 1-5 are in very bad conditions
>(bridge close down to seriously deteriorated). The rest from 6-10
>are categorized as good condition.However, the proportion of samples
>in my data are as follows. Bridges with 1-5 scale covers about 2-3%
>of total population. The majority of the bridges are in 7-8.
>Certainly, I have enough data for model estimation but the mix of
>the proportion is good. I attached the detail of condition rating
>scale at the end of this message.
><snip>

My guess is that you really have two distributions here: 1) Bridges that are basically under proper supervision and repair (Categories 6-10), and those that are not Categories 1-5). These two classes would probably have dramatically different relations to the covariates your are using.

So my recommendation would be to consider splitting your response into two classes (0/1), each with 5 sub categories.

Keeping the two classes merged together in a single group is equivalent to merging two different distributions with a weighting factor. This may be causing a bimodal distribution which is giving you problems.

You could try your modeling on each of the two classes separately before continuing with your full dataset modeling. You may learn something useful to help you with your problems.

For the full model, you would need to include a full set of interaction terms with "class".



Robert A. LaBudde, PhD, PAS, Dpl. ACAFS e-mail: ral_at_lcfltd.com
Least Cost Formulations, Ltd.            URL: http://lcfltd.com/
824 Timberlake Drive                     Tel: 757-467-0954
Virginia Beach, VA 23464-3239            Fax: 757-467-2947

"Vere scire est per causas scire"



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