|Date: ||Sun, 3 Mar 2002 00:55:48 +0000|
|Reply-To: ||Hayrettin OKUT <hokut@HOTMAIL.COM>|
|Sender: ||"SAS(r) Discussion" <SAS-L@LISTSERV.UGA.EDU>|
|From: ||Hayrettin OKUT <hokut@HOTMAIL.COM>|
|Subject: ||Re: Multinomial Logit ??|
|Content-Type: ||text/plain; format=flowed|
You can use latent class analysis (LCA) for get more homogenous segments or
For LCA in the structural portion of the model, the categorical latent
variables of C represent mixture components that are related to covariates
(X`s) through a multinomial logit regression model for an unordered
In multinomial logits, one of the segment (class) serves as the baseline or
reference category and we calculate logits for the other categories relative
to the reference category and then let the logits be a linear function of
However, because latent class analysis uses a multinomial logit for
determining differences between classes , this approach ignores
interindividual differences that exist within classes. That is, response
probabilities for all individuals of a given class are identical.
For SAS procedure see "A SAS Procedure Based on Mixture Models for
Estimating Developmental Trajectories" Jones and at el.,
>From: Brad Branford <b_branford@YAHOO.COM>
>Reply-To: Brad Branford <b_branford@YAHOO.COM>
>Subject: Multinomial Logit ??
>Date: Fri, 1 Mar 2002 20:38:52 -0800
>I need some advice.
>I'm trying to build a predictive model for prospective account-holders
>in my industry. Here's what I'm planning on doing:
>1) Take a random sample of current account-holders and segment them (3
>or 4 groups) based on certain internal performance criteria.
>2) Build a multinomial logit model with the segment being the
>dependent variable and prospect external data (at the time of
>acquisition) as explanatory variables.
>3) Use the model to segment prospects at the time of acquisition.
>However, I had a few questions:
>a) In a multinomial logit setting, how do I use the model predictions
>b) If I plan to use SAS, which procedure should I use?
>Thanks a lot in advance.
Chat with friends online, try MSN Messenger: http://messenger.msn.com