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From |
Stas Kolenikov <skolenik@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: svy + aweights |

Date |
Thu, 10 Nov 2011 15:39:48 -0500 |

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 >>>>> * >>>>> * 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/ > -- Stas Kolenikov, also found at http://stas.kolenikov.name Small print: I use this email account for mailing lists only. * * 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>

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