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Re: st: Controlling for atrittion in panel, or creating a panel without atrittion

From (Brendan Halpin)
Subject   Re: st: Controlling for atrittion in panel, or creating a panel without atrittion
Date   Thu, 23 Feb 2012 10:31:30 +0000

On Thu, Feb 23 2012, Laurie Molina wrote:

> 1. To take a random sample at the first period and then merge the
> databases to have a panel. In this case my panel will have attrition.
> In fact by the last period the attrition rate (comparing period 1
> observations with period 10 observations will be of almost 50%). The
> remaining sample size much smaller than the original sample size is
> leading to representativeness issues.

Yes, your sub-sample will have attrition bias, but in a way that
reflects that of your main sample. That is, if your main sample is
representative in wave 1 and then suffers from attrition, this is
probably a good option, but if subjects can meaningfully enter the main
sample after wave 1 perhaps not.

> 2. To take a random sample of the observations that appear on the
> database in all the periods. If attrition is not random, then i would
> have a population that is different to the original population, and
> hence my random sample may not be representative for the original
> population, but only for the population defined by all the
> observations that appear in the database in all periods.

Depending on what analysis you do afterwards, you may end up imposing
this restriction anyway. 

> Which option do you think i should take?

A third option would be to take a random sample of IDs, and take all
observations available for them. This will better replicate the pattern
of missingness in the main sample.

Which option is best depends on what analysis you want to do, and on how
the main sample is collected (in particular, in what way and at what
time it is representative), 

Brendan Halpin,   Department of Sociology,   University of Limerick,   Ireland
Tel: w +353-61-213147  f +353-61-202569  h +353-61-338562;  Room F1-009 x 3147    ULSociology on Facebook:         twitter:@ULSociology
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