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Re: st: Bootstrap command when used with cluster and strata options


From   "Chris Frost" <Chris.Frost@lshtm.ac.uk>
To   "statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu>
Subject   Re: st: Bootstrap command when used with cluster and strata options
Date   Thu, 24 Oct 2013 11:14:31 +0100

Dear Nick
 
Thanks for your input but I am afraid that I don't agree with you. Stata is giving different subjects (from different strata) the same "newid" in the bootstrap samples. There is nothing in the code that I (or Austin) have used that implies that this should be the case. Austin's program illustrates this nicely: if you run it you get 
 
. list
 
 +--------------------+
 | s   i   newid    c |
 |--------------------|
  1. | 0   5   1    1 |
  2. | 0   6   2    2 |
  3. | 0   7   3    3 |
  4. | 0   7   4    4 |
  5. | 0   9   5    5 |
 |--------------------|
  6. | 0   9   6    6 |
  7. | 1   1   1    7 |
  8. | 1   1   2    8 |
  9. | 1   3   3    9 |
 10. | 1   4  4   10 |
 +--------------------+
 
The first and seventh (and second and eighth etc.) subjects share the same "newid", but they are not the same subject. The creation of "c" corrects this, but should not be needed - this is, in my view, a software error. The "fix" that I would like would make this correction automatic.   

Chris

Chris Frost
Professor of Medical Statistics
Department of Medical Statistics
London School of Hygiene and Tropical Medicine
+44(0)20 7927 2242

>>> Nick Cox <njcoxstata@gmail.com> 24/10/2013 10:56 >>>
Hmmm... So, what would the "fix" be?  At first sight, you asked for
something you didn't want. It's difficult for Stata to know that.

Nick
njcoxstata@gmail.com 


On 24 October 2013 10:31, Chris Frost <Chris.Frost@lshtm.ac.uk> wrote:

Thanks for the succinct illustration of the problem and neat "get
round" using egen.  I do think that this is a trap for the unwary
though and should really be fixed in the software (I can conceive of
no situation where newid needs to be crossed with strata in the
bootstrap samples - and plenty of situations where the introduction of
this artificial sharing of newid across strata will cause errors if
not corrected).

Austin Nichols <austinnichols@gmail.com> 23/10/2013 19:10

> No need, I can see what you mean in a simple example:
>
> clear
> set seed 1
> set obs 10
> g s=_n<5
> g i=_n
> bsample, strata(s) cluster(i) idcluster(newid)
> egen c=group(s newid)
> list
>
> and I assume you need a newid that can act as a identifier across
> strata, so you need to generate a c as above.  You can wrap your
> commands to bootstrapped in a -program- and bootstrap it.

On Wed, Oct 23, 2013 at 12:30 PM, Chris Frost <Chris.Frost@lshtm.ac.uk> wrote:

Thanks for your reply - but I do think the problem is with the
program, not with the data. In my data clusters (id) do not cross
strata (group) - the problem is that in each bootstrap sample that is
created the created cluster variable (newid) DOES (erroneously) cross
strata. This can be seen if the bootstrap is run with the "noisily"
option. If you are interested in seeing the behavior I can send you an
annotated do file that illustrates the problem?

Austin Nichols <austinnichols@gmail.com> 23/10/2013 16:42 >>>

>> Sounds like a problem with your data to me, not the program. If your
>> clusters seem to cross strata, because of the coding in your data, you
>> can define a new cluster variable
>> egen newc=group(group id)
>> or you can specify that clusters are defined by two variables
>> bootstrap, strata(group) cluster(group id) idcluster(newid):

On Wed, Oct 23, 2013 at 6:11 AM, Chris Frost <Chris.Frost@lshtm.ac.uk> wrote:

I think that there is a problem with the bootstrap command when used
in conjunction with the "cluster" and "strata" options. The problem
arises because the command "bootstrap, strata(group) cluster(id)
idcluster(newid) ....." creates a variable "newid" which is only
unique (at the cluster level) within each strata. For example if there
are 1000 subjects (with multiple measures per subject) each with a
unique id but in two equal size groups the above command will result
in each bootstrap sample having only 500 values of newid with subjects
being erroneously paired up: this will lead to incorrect variance
estimates with a command such as bootstrap, strata(group) cluster(id)
idcluster(newid): mixed outcome i.group || newid:

Am I correct? Can this be fixed?
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