Dear Luis,
assuming that the last observation only is missing for each individual (if
this is the case, your analysis would be affected by a limited bias), can't
you simply right-censor the survival analysis at wave #7 (provided that all
the individuals have the same probability of being right-censored)?
Should the previous hint be unfeasible, I would refer you to the following
article, hopefully of some help:
Pfeifer PE, Bang H (2005) Non-parametric estimation of mean customer
lifetime value. Journal of Interactive Marketing. Doi:10.1002/dir.20049
Kind Regards,
Carlo
-----Messaggio originale-----
Da: [email protected]
[mailto:[email protected]] Per conto di Luis Ortiz
Inviato: lunedì 7 settembre 2009 18.43
A: [email protected]
Oggetto: st: Loss of observations with lagged variables in survival analysis
I am using information on wages for an event-history (survival) analysis.
This information needs to be lagged forward. As a result, the latest
observation of this variable for each individual is missing. Here I post an
example for a given individual of my sample:
pid wave wage wage_lag
20102 1 1577.2 1712.125
20102 2 1712.125 2242.275
20102 3 2242.275 1934.929
20102 4 1934.929 2298.635
20102 5 2298.635 2493.237
20102 6 2493.237 2667.933
20102 7 2667.933 3341.879
20102 8 3341.879 .
This has an effect on my analysis. Introducing this lagged variable in the
analysis automatically means losing observations, since the lagged variable
does not exist for the latest observation, as you may see above. This is
rather unfortunate, since some of these periods are the latest ones in my
spells of analysis.
Is there any way of coming over this problem you come up with?
Many thanks for your attention
Luis
-.-.-.-.-.-.-.-
Luis Ortiz
Profesor Agregado
Departament de Ciencies Polítiques i Socials
Universitat Pompeu Fabra
Ramon Trias Fargas, 25-27
08005 Barcelona
Phone: +34-93-5422368
Fax: +34-93-5422372
http://www.upf.edu/dcpis/
http://sociodemo.upf.edu/
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