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st: rediting Outreg2 results


From   Lucas Ferreira Mation <[email protected]>
To   statalist <[email protected]>
Subject   st: rediting Outreg2 results
Date   Mon, 25 Jul 2011 15:47:59 -0300

Dear Stata-listers,
I´m seeking advice from more experienced users on how to use outreg2
to make final adjustments to publication quality tables (of regression
estimates). I´ve search the "statalist" and "help" but did not find a
more recent and definitive result. My questions:


1) Currently use outreg2 and then do the final editing in Excel. That
works but can be quite time consuming and repetitive.
What do most people do?

2) Is it possible to edit regression tables in Stata if you just have
the tables but not the original database? I´m using confidential data,
which means I only get access to estimate results (descriptive stats,
regression tables, etc). I wanted to know if it is possible to execute
"outreg2" again for formatting the tables for publication without
having to re execute any additional regression (e(b) and related
matrix are empty). If unclear see example bellow using "auto.dta".

thank you in advance.
Lucas Mation
Ipea-Brasil


* I go to the "restricted data" room and execute:
webuse auto.dta, clear
reg price mpg
outreg2 using REG_RESULTS
reg price mpg rep78 headroom trunk weight
outreg2 using REG_RESULTS

clear all // the confidentiality committee approves release of the
REG_RESULTS file. Thus that is all I have, not the original data
(auto.dta)


* Suppose I only want to display the variables in the final table: mpg
rep78  .Is there a way to use something like:

outreg2 mpg rep78 using REG_RESULTS // notice that at this point there
is no estimate stored at e(b), I am just trying to use outreg2 for
editing. Is there any option to avoid the result: "matrix e(b) not
found; run or post a regression first"

*OBS: of course i could add a "fake regression" in order to allow
outreg2 to work again
set obs 3
gen y=1
gen mpg=.
gen rep78=.
reg y // any variable
outreg2 mpg rep78 using REG_RESULTS
* then open in Excel and delete the last column (the fake regression results)

*
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