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st: Simple regression and Multiple regression?
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statalist<[email protected]>
Subject
st: Simple regression and Multiple regression?
Date
Sun, 14 Mar 2010 17:41:24 +0800
Dear statalists,
Suppose there are situations as follows,
situation1:
reg y x1 x2 x3 x4
situation2:
reg y x1 x2 x3
predict re,re
reg re x4
Whether the coefficients and significance on x4 in two situations are the same in fact though a little difference in decimal part?
The results of a random sample are as follows,
situation1:coefficient=-.0039743 significance=0.675
situation2:coefficient=-.0038959 significance=0.677
reg y x1 x2 x3 x4
Source | SS df MS Number of obs = 278
-------------+------------------------------ F( 4, 273) = 15.88
Model | .309280434 4 .077320108 Prob > F = 0.0000
Residual | 1.32893274 273 .004867885 R-squared = 0.1888
-------------+------------------------------ Adj R-squared = 0.1769
Total | 1.63821317 277 .005914127 Root MSE = .06977
------------------------------------------------------------------------------
y | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
x1 | .1284174 .0299903 4.28 0.000 .0693757 .1874591
x2 | .0617595 .0393121 1.57 0.117 -.0156338 .1391529
x3 | .0131323 .0020908 6.28 0.000 .0090162 .0172484
x4 | -.0039743 .0094827 -0.42 0.675 -.0226428 .0146943
_cons | .0603695 .011657 5.18 0.000 .0374204 .0833185
------------------------------------------------------------------------------
. reg y x1 x2 x3
Source | SS df MS Number of obs = 278
-------------+------------------------------ F( 3, 274) = 21.18
Model | .308425392 3 .102808464 Prob > F = 0.0000
Residual | 1.32978778 274 .00485324 R-squared = 0.1883
-------------+------------------------------ Adj R-squared = 0.1794
Total | 1.63821317 277 .005914127 Root MSE = .06967
------------------------------------------------------------------------------
y | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
x1 | .1280548 .0299327 4.28 0.000 .0691275 .1869822
x2 | .0638026 .0389499 1.64 0.103 -.0128765 .1404818
x3 | .0130832 .0020844 6.28 0.000 .0089799 .0171866
_cons | .0588763 .0110825 5.31 0.000 .0370586 .0806941
------------------------------------------------------------------------------
. predict re,re
. reg re x4
Source | SS df MS Number of obs = 278
-------------+------------------------------ F( 1, 276) = 0.17
Model | .000838193 1 .000838193 Prob > F = 0.6768
Residual | 1.32894959 276 .004815035 R-squared = 0.0006
-------------+------------------------------ Adj R-squared = -0.0030
Total | 1.32978778 277 .004800678 Root MSE = .06939
------------------------------------------------------------------------------
re | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
x4 | -.0038959 .0093377 -0.42 0.677 -.0222781 .0144862
_cons | .0010651 .0048823 0.22 0.827 -.0085462 .0106763
------------------------------------------------------------------------------
Thank you for any help!
Best regards,
Rose
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