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RE: st:Survival analysis - dealing with Right truncated data


From   "Phakathi, T.R." <[email protected]>
To   "[email protected]" <[email protected]>
Subject   RE: st:Survival analysis - dealing with Right truncated data
Date   Fri, 17 Aug 2012 19:22:27 +0000

Thanks Steve, Nick - feedback appreciated

________________________________________
Van: [email protected] [[email protected]] namens Steve Samuels [[email protected]]
Verzonden: vrijdag 17 augustus 2012 20:56
To: [email protected]
Onderwerp: Re: st:Survival analysis - dealing with Right truncated data

Dear Themba:

I have no specific advice to offer because your options depend on what
information can be obtained (or estimated or assumed) about employment at the
firms from which your data set is drawn. Since you are at VU University
Amsterdam, I suggest that you seek assistance from faculty there. A quick
look at the University web site shows that sophisticated work is done in
the Faculty of Social Sciences, at least. I'm sorry that I can't be of
further help.

Good luck!


Steve


On Aug 17, 2012, at 2:03 PM, Phakathi, T.R. wrote:

Steve, is there a way out of this - what can be done?

________________________________________
Van: [email protected] [[email protected]] namens Steve Samuels [[email protected]]
Verzonden: vrijdag 17 augustus 2012 16:59
To: [email protected]
Onderwerp: Re: st:Survival analysis - dealing with Right truncated data

Because you utilize no information about those who did not fail, you can
say _nothing_ about the impact of covariates on survival.

Example: compare 2 groups

1. Your data

Failures
Group 1:   1 2
Group 2:   9 10

What can be said: of those who failed, failures in group 2
were later.  But this does _not_ mean that survival was
better in group 2.

2. Complete Data

Group 1: Failures 1 2   Not Failed 11 12 13
Group 2: Failures 9 10  Not failed 0

Percent who failed through T = 10
Group 1  20%
Group 2  100%

Steve
[email protected]



On Aug 17, 2012, at 10:15 AM, Phakathi, T.R. wrote:

The dataset ONLY includes observations that have failed (Right truncation). For those that have failed (in this case all who lost employment), there are details on the risk onset and failure date including individual and firm characteristics.

I would like to estimate the impact of the covariates on Survival. Are the commands distinct from “normal” survival data? If so what are the available commands (Non/Semi &parametric)?

May I tap into the wealth of your experiences


Thank you

Themba Phakathi
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