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Re: st: svy + aweights
From
Jeph Herrin <[email protected]>
To
[email protected]
Subject
Re: st: svy + aweights
Date
Thu, 10 Nov 2011 16:05:19 -0500
I would be downweighting the subjects with fewer days; in practice,
I wouldn't actually use number of days but the inverse of the variance
of the daily average, since I have that, number of days is just a short
hand way of thinking about it.
Not all obese kids have less days than normal kids, it's just that
the distribution is skewed down - higher percent with 1-2 days and
lower percent with 6-7 days.
On 11/10/2011 3:37 PM, Joerg Luedicke wrote:
Then it seems to be a problem of reliability of your measure, i.e.,
measurement for obese kids is less reliable than measurement for
non-obese kids, right? Now, if you upweight the obese kids in your
sample, why would that enhance the reliability of their measurement?
If I understand the problem correctly, then weighting strikes me as
the wrong approach here.
Perhaps you could consider not averaging at all and running a
multilevel model of some sort.
J.
On Thu, Nov 10, 2011 at 3:23 PM, Jeph Herrin<[email protected]> wrote:
For each day, I have 1440 minutes (24 hours) of measurements. Each minute
has an activity measure, 0-30,000. I want to compare how active the kids
(these are all children) are, so I calculate an activity measurement for
each day (to keep it simple here I will say it is the median, though
actually
it is a complicated function of the activity levels over the day).
id day1 day2 day3 obese average days
1 500 500 500 Y 500 3
2 1000 N 1000 1
Now I want to compare kids who are normal weight to those who are
obese. It turns out, I don't have as many measurements on the obese
kids because they did not wear their monitor as often. So the
active kids have more precise daily averages than the obese kids.
To compare average activity, I want to account for the differences
in precision.
If this was not -svy- data, I would use something like
ttest average [aw=days], by(obese)
even better -reshape- the data to have one record per day per id and use
xtset id
xtreg average
But here I have this complex survey design to deal with.
thanks,
Jeph
On 11/10/2011 3:06 PM, Joerg Luedicke wrote:
I do not quite understand what you are trying to do. Suppose we have
two individuals, one measured only once and the other on, say, 3
occasions. Let's further assume that activity is measured in minutes
(btw, how is your dependent variable measured?). We could have the
following data:
id day1 day2 day3
1 30
2 10 10 10
If you calculate the minutes per day now (whether or not this being a
proper way of handling it), id#1 will end up with 30 and id#2 with 10
minutes. I do not understand why id#2 is supposed to weigh more than
id#1?
J.
On Thu, Nov 10, 2011 at 2:34 PM, Jeph Herrin<[email protected]> wrote:
Thanks for the suggestion, but I specifically need to give more
weight to subjects which have more days of observation. For example,
I have
svy : regress activity female BMI
and would like this regression to give more weight to subjects which
have more days of observation. Using activity/days as the dependent
variable will not do this.
Jeph
On 11/10/2011 1:58 PM, Stas Kolenikov wrote:
Rather than forming the mean activity per day, you might want to
analyze this as a ratio:
svy : ratio activity / day_reported
or whatever would be an appropriate ratio. That way, you will get
correct standard errors without messing with the analytical weights.
On Thu, Nov 10, 2011 at 1:46 PM, Jeph Herrin<[email protected]>
wrote:
I am analyzing NHANES data (see manual page for -svyset-) using -svy-
commands. My complication is that I am using the subset of subjects for
which there is activity monitoring, and the number of days monitored
varies
from 1 to 8. So - to be clear - for some subjects I have 1 day of
monitoring,
and for some I have 2 days, some I have 3, etc. My dependent variable
of
interest is daily average activity levels, but I would like this to be
weighted by the number of days monitored. (This is important because
there
seems to be a clear relationship between days monitored and age, race,
etc).
How do I incorporate this additional level of weighting? For instance,
if I use
svy : mean depvar [aw=days]
I get an error that weights are not reported.
thanks,
Jeph
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