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

2007-06-17 Thread adschai
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

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

2007-06-17 Thread Robert A LaBudde
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

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

2007-06-16 Thread adschai
Thank you so much Robert. I haven't thought about the idea of clumping categories together. One of the reason is because these categories are bridge condition rating scores. They indeed represent different meaning and serviceability conditions. They vary from 0-9. I have about 300,000 data in

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

2007-06-16 Thread Robert A LaBudde
At 03:17 AM 6/16/2007, adschai wrote: Thank you so much Robert. I haven't thought about the idea of clumping categories together. One of the reason is because these categories are bridge condition rating scores. They indeed represent different meaning and serviceability conditions. They vary

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

2007-06-15 Thread adschai
Hi, I have a model which tries to fit a set of data with 10-level ordered responses. Somehow, in my data, the majority of the observations are from level 6-10 and leave only about 1-5% of total observations contributed to level 1-10. As a result, my model tends to perform badly on points that

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

2007-06-15 Thread Robert A LaBudde
At 09:31 PM 6/15/2007, adschai wrote: I have a model which tries to fit a set of data with 10-level ordered responses. Somehow, in my data, the majority of the observations are from level 6-10 and leave only about 1-5% of total observations contributed to level 1-10. As a result, my model tends