Re: st: proper use of aweight

[Steve Samuels <sjsamuels@gmail.com>]

Welcome, Carlianne!

As Austin states, aweights are quite versatile. Two faux pas to avoid in the future:

1. "Precise literature references, please" (FAQ 3.4), not "some published papers". http://www.stata.com/support/faqs/res/statalist.html#others)

2. Stata should not be spelled "STATA" (FAQ 4.2). 
http://www.stata.com/support/faqs/res/statalist.html#spell

In contrast, "SAS","SPSS", and "SUDAAN" are correct spellings because 
they are acronyms for the original names:

SAS = "Statistical Analysis System"
SPSS = "Statistical Package for the Social Sciences"
SUDAAN = "SUrvey DAta ANalysis"

Steve
sjsamuels@gmail.com



On Apr 19, 2012, at 6:21 PM, Carlianne Patrick wrote:

I am new to STATAlist, so please excuse any posting faux pas I may make in my initial posting(s). Also, thank you in advance for any help.

I am using STATA11.2; however, my question is regarding the posted code from some published papers (and thus I don't know which version they were using). I would like to use the techniques in these papers for my analysis, but am concerned that the code isn't doing what the papers say it is doing.

After reading the available STATA documentation on aweight, it appears that this particular weighting option is really only suitable when the observations are means of underlying data. However, in the posted codes it is used to accomplish one of two things:
1) Weight the data with lagged values of the dependent variable.
2) Weight "matches" by the inverse of their number or log odds ratio (specifically, in situations where multiple untreated observations are "matched" to one treated observation).

I may misunderstand what aweights is doing. If not, then it appears that it is not the appropriate weighting option command to accomplish (1) or (2) if you are weighting by the log odds ratio. It seems appropriate only if you have already taken the average of the matches. Then, the average of the matches could by weighted by their number and the treated observation weighted by 1.

Is this the correct interpretation?

If it isn't, is there a reference that might help me understand why aweight is appropriate in these situations?

Best wishes,
Carlianne

Carlianne Patrick, CEcD
PhD Candidate
Department of Agricultural, Environmental, and Development Economics
The Ohio State University

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