[Date Prev][Date Next][Thread Prev][Thread Next][Date index][Thread index]

From |
Steven Samuels <sjhsamuels@earthlink.net> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: re; st: Pweight |

Date |
Thu, 18 Sep 2008 11:33:49 -0400 |

Gao-- you might have missed this in the -help-. Notice the section set off by ** **'s.

-Steve

"aweights, or analytic weights, are weights that are inversely proportional to the variance of an observation; i.e., the

variance of the jth observation is assumed to be sigma^2/ w_j, where w_j are the weights. **Typically, the observations

represent averages and the weights are the number of elements that gave rise to the average"**

On Sep 18, 2008, at 11:15 AM, Gao Liu wrote:

Thanks, Steve and Austin, I did check the help for weight,but had not much idea which type of weight, if any, is appropriate. It is my first time to deal with weight option. Austin's suggestion is great. I'll check how it works. Any other suggestions will be welcome Best Gao On Thu, Sep 18, 2008 at 10:22 AM, Steven Samuels <sjhsamuels@earthlink.net> wrote:"Should we use the pweight option in the regression?"

It appears that Gao did not consult -help weight-, where there is a clear

answer to his question.

-Steve

"Gao Liu" <gao.liu@gmail.com> wrote:We are estimating the impact of an intervention on the practice of

health providers. One outcome measure is the ratio of metformin

prescribed to diabetic patients. This ratio is defined as the ratio

between the number of diabetic patients prescribed with metformin and

the total number of diabetic patients treated by the provider. We try

to examine whether metformin ratios are different for treatment group

and unexposed group before and after the intervention date. Xtgee is

used to estimate the impact of the intervention.

But there is a problem: the number of diabetic patients varies a lot

from one provider to another. Some had only one or two diabetic

patients in a quarter, while others had more than 50. If a provider

has only 2 diabetic patients, one of whom was prescribed with

Metformin, then one patient's drop from being prescribed with

metformin would lead to a change of 50% in the metformin ratio. In

contrast, a health provider with 100 diabetic patients will have very

stable metformin ratio. Thus, it is inappropriate to treat all

providers the same in the regression.

Should we use the pweight option in the regression? Or is there any

other better approach that works for this study? Thank you

Be * * 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/

**References**:**re; st: Pweight***From:*Steven Samuels <sjhsamuels@earthlink.net>

**Re: re; st: Pweight***From:*"Gao Liu" <gao.liu@gmail.com>

- Prev by Date:
**st: The command "gentrun"** - Next by Date:
**RE: st: Comparing datasets** - Previous by thread:
**Re: re; st: Pweight** - Next by thread:
**st: -replace- should not be use with temporary files (was: Comparing datasets)** - Index(es):

© Copyright 1996–2015 StataCorp LP | Terms of use | Privacy | Contact us | What's new | Site index |