[R] covariate selection?

Hello, I am hoping someone can help me with the following multivariate issue: I have a model consisting of about 50 covariates. I would like to reduce this to about 5 covariate for the reduced model by combining cofactors that are strongly correlated. Is there a package or function that

RE: [R] covariate selection?

Col. Centro 06059 México, D. F. Tel. +52 55 52.37.20.00 ext. 3594 Fax. +52 55 52.37.27.03 e-mail: [EMAIL PROTECTED] -Mensaje original- De: Ian Fiske [mailto:[EMAIL PROTECTED] Enviado el: Martes, 12 de Octubre de 2004 04:08 PM Para: [EMAIL PROTECTED] Asunto: [R] covariate selection

Re: [R] covariate selection?

PM Para: [EMAIL PROTECTED] Asunto: [R] covariate selection? Hello, I am hoping someone can help me with the following multivariate issue: I have a model consisting of about 50 covariates. I would like to reduce this to about 5 covariate for the reduced model by combining cofactors

Re: [R] covariate selection?

Have you considered stepwise regression, e.g., step or stepAIC in library(MASS)? The documentation for both contain examples. hope this helps. spencer graves Ian Fiske wrote: Hello, I am hoping someone can help me with the following multivariate issue: I have a model

RE: [R] covariate selection?

this help you. Greetings, Juan Carlos -Mensaje original- De: Ian Fiske [mailto:[EMAIL PROTECTED] Enviado el: Martes, 12 de Octubre de 2004 05:17 PM Para: Martínez Ovando Juan Carlos CC: [EMAIL PROTECTED] Asunto: Re: [R] covariate selection? Thanks Juan. I thought

RE: [R] covariate selection?

Hi Ian Have you tried help.search(pca)? Christian -Original Message- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf Of Martínez Ovando Juan Carlos Sent: Tuesday, October 12, 2004 7:56 PM To: Ian Fiske Cc: [EMAIL PROTECTED] Subject: RE: [R] covariate selection? Hello Ian

Re: [R] covariate selection?

Ian Fiske wrote: Hello, I am hoping someone can help me with the following multivariate issue: I have a model consisting of about 50 covariates. I would like to reduce this to about 5 covariate for the reduced model by combining cofactors that are strongly correlated. Is there a package or

RE: [R] covariate selection?

PROTECTED] Subject: Re: [R] covariate selection? Ian Fiske wrote: Hello, I am hoping someone can help me with the following multivariate issue: I have a model consisting of about 50 covariates. I would like to reduce this to about 5 covariate for the reduced model by combining cofactors

Re: [R] covariate selection in cox model (counting process)

On Wed, 28 Jul 2004, Mayeul KAUFFMANN wrote: No, I mean recurrent events. With counting process notation but no recurrent revents the partial likelihood is still valid, and the approach of treating it as a real likelihood for AIC (and presumably BIC) makes sense. Roughly speaking, you

[R] covariate selection in cox model (counting process)

If you can get the conditional independence (martingaleness) then, yes, BIC is fine. One way to check might be to see how similar the standard errors are with and without the cluster(id) term. (Thank you again !, Thomas.) At first look, the values seemed very similar (see below, case 2).

Re: [R] covariate selection in cox model (counting process)

On Wed, 28 Jul 2004, Mayeul KAUFFMANN wrote: If you can get the conditional independence (martingaleness) then, yes, BIC is fine. One way to check might be to see how similar the standard errors are with and without the cluster(id) term. (Thank you again !, Thomas.) At first look,

Re: [R] covariate selection in cox model (counting process)

On Tue, 27 Jul 2004, Mayeul KAUFFMANN wrote: Thank you a lot for your time and your answer, Thomas. Like all good answers, it raised new questions for me ;-) In the case of recurrent events coxph() is not using maximum likelihood or even maximum partial likelihood. It is maximising the

[R] covariate selection in cox model (counting process)

No, I mean recurrent events. With counting process notation but no recurrent revents the partial likelihood is still valid, and the approach of treating it as a real likelihood for AIC (and presumably BIC) makes sense. Roughly speaking, you can't tell there is dependence until you see multiple

[R] covariate selection in cox model (counting process)

Hello everyone, I am searching for a covariate selection procedure in a cox model formulated as a counting process. I use intervals, my formula looks like coxph(Surv(start,stop,status)~ x1+x2+...+cluster(id),robust=T) where id is a country code (I study occurence of civil wars from 1962 to 1997).

Re: [R] covariate selection in cox model (counting process)

On Mon, 26 Jul 2004, Mayeul KAUFFMANN wrote: Hello everyone, I am searching for a covariate selection procedure in a cox model formulated as a counting process. I use intervals, my formula looks like coxph(Surv(start,stop,status)~ x1+x2+...+cluster(id),robust=T) where id is a country code

[R] covariate selection in cox model (counting process)

Thank you a lot for your time and your answer, Thomas. Like all good answers, it raised new questions for me ;-) In the case of recurrent events coxph() is not using maximum likelihood or even maximum partial likelihood. It is maximising the quantity that (roughly speaking) would be the partial