Re: Survival analysis using random regression

Dear Jose

I suspect there are several forms of survival analysis.
I understand in your case that each individual is represented by 52
lines of data and survival switches from 1 to 0 somewheerre through the
period of 52 days.

Do you have a reasonable number of families (= dams I gather)
 
Assuming you have a good number of individuals,
I would probably start by looking at the overall profile of survival
i.e. ignore genetics to start with. Is death linear with time?
Some kind of sigmoid curve is more likely is it not.

Then I would add ID to the model since this represents just a mean
shift. Then add dam to see if there is a genetic component to the
individual vasriation.

Only if you have a lot of individuals and families would I attempt the
change of slope at the genetic level.

See below

On Fri, 2009-10-16 at 01:19 +0100, jozzeman wrote:
> Hi,
>
> I'm trying to analyse survival data using a random regression model,
> but I have some problems interpreting the results. The data structure
> in the data file is as follows:
>
> ID father mother GDP1 Tank GDP2 day SR
> A440 1 3 0.8 1 0.2 1 1
> A440 1 3 0.8 1 0.2 2 1
> A440 1 3 0.8 1 0.2 3 0
> : : : : : : : :
> : : : : : : : :
> A440 1 3 0.8 2 0.2 52 0
> B550 1 3 0.5 2 0.4 1 1
> B550 1 3 0.5 2 0.4 2 1
>
>
>
>
> Reading the data is as follows:
>
> Survival analysis
> ID !P
> father
> mother
> GDP1 !m-9.9 # average daily gain before challenge to disease
> Tank # 2 levels
> GDP2 !m-9.9 # average daily gain after challenge to disease
> day # days of challenge tests (from 1 to 52)
> SR # survival score at a given day (1 or 0 depending if individual
> is alive or dead in a specific day)
> sr2.txt !ALPHA !REPEAT
> sr2.txt !NODISPLAY !MVINCLUDE !SKIP 1 !maxiter=500
>
> I started fitting the follow model:
>
> SR ~mu pol(day,1)*Tank !r pol(day,1).mother !f mv

For this to work, 'mother' should be a 'FACTOR'.
but I think the model needs ide(ID) first.

> 0 1 1

This shuld be
0 0 1
>
> pol(day,1).mother 2
> pol(day,1) 0 US .1 .01 1 !GP
> mother
>
> I am interested in estimating the genetic variance of the family (full
> sibs) this is why I am including only the random effect associated
> with mother effect.
>
> Am I in the right way?
See above
> See above
>
> Can I use !BINOMIAL and !LOGIT qualifiers in the model in order to
> take account the binary nature of the trait?
>
YES but I would concentrate on a plausible model on the 0,1 scale first.

> How can I estimate heritabilities for SR?
>
Lets get the model sorted, and sensible from a genetic perspective
first. Then it should be clearer.

> How can I fit a multivariate analysis for estimating the genetic
> correlation between SR and GDP2?
>
> I would appreciate very much any suggestions or comments about the
> coding for the analysis.
>
> Thanks in advance!
>
> José
>
>
>
>
> -------------------- m2f --------------------
>
> Sent using Mail2Forum (http://www.mail2forum.com).
>
> Read this topic online here:
> http://www.vsni.co.uk/forum/viewtopic.php?p=945#945
>
> -------------------- m2f --------------------
>
>
>
>
> This message is intended for the addressee named and may contain confidential information. If you are not the intended recipient, please delete it and notify the sender. Views expressed in this message are those of the individual sender, and are not necessarily the views of their organisation.

-- 
Best Wishes,
Arthur Gilmour
Adjunct Professor
School of Computing and Mathematics
Charles Sturt University
Jesus went to the synagogue in every town in Galilee to preach and drive
out demons.
A leper came, knelt down and said, "If you will, you can make me clean".
Jesus was moved. He reached out and touched him and said 
"I am willing.  Be clean." He was cleansed immediately.
Mobile Number +61 427 227 468
Home phone +61 2 6364 3288  Skype: Arthur.Gilmour
http://www.CargoVale.com.au/asreml
Travel:
Adelaide AAABG 27Sept to 2 Oct
         ASReml workshop 6-8 Oct
Brisbane Probe 29Nov to 6 Dec
Bangladesh Prosihhkon 31Dec - 31 Jan