Re: st: svy + aweights

[Stas Kolenikov <skolenik@gmail.com>]

You do need to -reshape long-, and then you can do any analysis with
these daily measures. E.g., you could -svy : mean daily_outcome ,
over(obese)-. Since the latter is an estimation command, you'd be able
to form (a version of) the t-test by the standard post-estimation
-test- command. I don't think you need any averaging here at all.

On Thu, Nov 10, 2011 at 3:23 PM, Jeph Herrin <stata@spandrel.net> 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<stata@spandrel.net>  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<stata@spandrel.net>
>>>>  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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-- 
Stas Kolenikov, also found at http://stas.kolenikov.name
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