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From |
Joerg Luedicke <joerg.luedicke@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: svy + aweights |

Date |
Thu, 10 Nov 2011 16:28:58 -0500 |

> I would be downweighting the subjects with fewer days; Whether you downweight subjects with fewer days or upweight subjects with more days should be the same thing. Anyway, if your concern is that of differing reliability across sub-groups of your data, then weighting will not solve the problem. > 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. I am completely at a loss with this one. > > 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. As I said, consider a multilevel model. That way you can directly account for the uncertainty that is related to the varying numbers of measurement occasions. J. > > 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<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 >>>>>>> * >>>>>>> * For searches and help try: >>>>>>> * http://www.stata.com/help.cgi?search >>>>>>> * http://www.stata.com/support/statalist/faq >>>>>>> * http://www.ats.ucla.edu/stat/stata/ >>>>>>> >>>>>> >>>>>> >>>>>> >>>>> * >>>>> * For searches and help try: >>>>> * http://www.stata.com/help.cgi?search >>>>> * http://www.stata.com/support/statalist/faq >>>>> * http://www.ats.ucla.edu/stat/stata/ >>>>> >>>> >>>> * >>>> * For searches and help try: >>>> * http://www.stata.com/help.cgi?search >>>> * http://www.stata.com/support/statalist/faq >>>> * http://www.ats.ucla.edu/stat/stata/ >>>> >>>> >>>> ----- >>>> No virus found in this message. >>>> Checked by AVG - www.avg.com >>>> Version: 2012.0.1869 / Virus Database: 2092/4607 - Release Date: >>>> 11/09/11 >>>> >>>> >>> * >>> * For searches and help try: >>> * http://www.stata.com/help.cgi?search >>> * http://www.stata.com/support/statalist/faq >>> * http://www.ats.ucla.edu/stat/stata/ >>> >> >> * >> * For searches and help try: >> * http://www.stata.com/help.cgi?search >> * http://www.stata.com/support/statalist/faq >> * http://www.ats.ucla.edu/stat/stata/ >> >> >> ----- >> No virus found in this message. >> Checked by AVG - www.avg.com >> Version: 2012.0.1869 / Virus Database: 2092/4607 - Release Date: 11/09/11 >> >> > * > * For searches and help try: > * http://www.stata.com/help.cgi?search > * http://www.stata.com/support/statalist/faq > * http://www.ats.ucla.edu/stat/stata/ > * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**Follow-Ups**:**Re: st: svy + aweights***From:*Jeph Herrin <stata@spandrel.net>

**References**:**st: svy + aweights***From:*Jeph Herrin <stata@spandrel.net>

**Re: st: svy + aweights***From:*Stas Kolenikov <skolenik@gmail.com>

**Re: st: svy + aweights***From:*Jeph Herrin <stata@spandrel.net>

**Re: st: svy + aweights***From:*Joerg Luedicke <joerg.luedicke@gmail.com>

**Re: st: svy + aweights***From:*Jeph Herrin <stata@spandrel.net>

**Re: st: svy + aweights***From:*Joerg Luedicke <joerg.luedicke@gmail.com>

**Re: st: svy + aweights***From:*Jeph Herrin <stata@spandrel.net>

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