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st: variable name abbreviations for all n-way factor variable interactions when using -testparm-
From
"Beede, David N" <[email protected]>
To
"'[email protected]'" <[email protected]>
Subject
st: variable name abbreviations for all n-way factor variable interactions when using -testparm-
Date
Fri, 6 Aug 2010 15:56:57 -0400
I am stumped by this notation problem.
If you are estimating n-way factorial specifications using factor variables and want to test if the coefficients for all m-way or greater interactions (where m <= n) are jointly equal to zero, why can't you do something like:
testparm *#*#*
(in the case where you are estimating, say 6-way factorial specification but want to test if all 3-way and higher interactions are zero)?
When I tried this (see example below) I got more than just the 3-way interactions. I know in the case of the example I could just do testparm group#sex#arm, but what if I have 8 (the maximum number of interactions allowed using factor variables and the ## notation) variables?
Thank you for any help you can provide!
David
. use http://www.stata-press.com/data/r11/fvex
(Artificial factor variables' data)
. regress y agegroup##sex##arm
Source | SS df MS Number of obs = 3000
-------------+------------------------------ F( 23, 2976) = 22.69
Model | 207587.375 23 9025.53803 Prob > F = 0.0000
Residual | 1183845.63 2976 397.797591 R-squared = 0.1492
-------------+------------------------------ Adj R-squared = 0.1426
Total | 1391433.01 2999 463.965657 Root MSE = 19.945
------------------------------------------------------------------------------
y | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
agegroup |
2 | 7.872115 8.063784 0.98 0.329 -7.939041 23.68327
3 | 1.795313 7.479324 0.24 0.810 -12.86986 16.46048
4 | -5.772757 7.404368 -0.78 0.436 -20.29096 8.745443
|
1.sex | 29.8375 7.499731 3.98 0.000 15.13232 44.54268
|
agegroup#sex |
2 1 | -10.86605 8.634784 -1.26 0.208 -27.79681 6.064697
3 1 | -8.05146 8.00574 -1.01 0.315 -23.74881 7.645886
4 1 | -8.217461 7.90107 -1.04 0.298 -23.70958 7.274653
|
arm |
2 | 12.10533 7.246137 1.67 0.095 -2.102614 26.31328
3 | 19.42648 7.126994 2.73 0.006 5.452143 33.40081
|
agegroup#arm |
2 2 | -8.279273 8.369064 -0.99 0.323 -24.68901 8.130464
2 3 | -7.253848 8.247162 -0.88 0.379 -23.42456 8.91687
3 2 | -3.18379 7.828699 -0.41 0.684 -18.534 12.16642
3 3 | -4.491854 7.768685 -0.58 0.563 -19.72439 10.74068
4 2 | -4.008206 7.850135 -0.51 0.610 -19.40045 11.38404
4 3 | -2.475406 8.000771 -0.31 0.757 -18.16301 13.2122
|
sex#arm |
1 2 | -11.87131 7.945362 -1.49 0.135 -27.45027 3.707648
1 3 | -13.01725 7.964627 -1.63 0.102 -28.63398 2.599485
|
agegroup#|
sex#arm|
2 1 2 | 10.41656 9.304878 1.12 0.263 -7.828081 28.66121
2 1 3 | 3.438556 9.717089 0.35 0.723 -15.61434 22.49145
3 1 2 | 3.063942 8.717606 0.35 0.725 -14.0292 20.15709
3 1 3 | -.2612288 9.452897 -0.03 0.978 -18.79611 18.27365
4 1 2 | 6.733436 8.711734 0.77 0.440 -10.3482 23.81507
4 1 3 | -3.543607 10.05656 -0.35 0.725 -23.26212 16.17491
|
_cons | 51.5625 7.051574 7.31 0.000 37.73605 65.38895
------------------------------------------------------------------------------
. testparm *#*#*
( 1) 2.agegroup = 0
( 2) 3.agegroup = 0
( 3) 4.agegroup = 0
( 4) 1.sex = 0
( 5) 2.agegroup#1.sex = 0
( 6) 3.agegroup#1.sex = 0
( 7) 4.agegroup#1.sex = 0
( 8) 2.arm = 0
( 9) 3.arm = 0
(10) 2.agegroup#2.arm = 0
(11) 2.agegroup#3.arm = 0
(12) 3.agegroup#2.arm = 0
(13) 3.agegroup#3.arm = 0
(14) 4.agegroup#2.arm = 0
(15) 4.agegroup#3.arm = 0
(16) 1.sex#2.arm = 0
(17) 1.sex#3.arm = 0
(18) 2.agegroup#1.sex#2.arm = 0
(19) 2.agegroup#1.sex#3.arm = 0
(20) 3.agegroup#1.sex#2.arm = 0
(21) 3.agegroup#1.sex#3.arm = 0
(22) 4.agegroup#1.sex#2.arm = 0
(23) 4.agegroup#1.sex#3.arm = 0
F( 23, 2976) = 22.69
Prob > F = 0.0000
David N. Beede, Ph.D.
Economist
Office of Policy Development
Economics & Statistics Administration
U.S. Department of Commerce
Office: Room 4872
Mailstop: Room 4858 HCHB
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