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| From | Richard Williams <richardwilliams.ndu@gmail.com> |
| To | statalist@hsphsun2.harvard.edu, <statalist@hsphsun2.harvard.edu> |
| Subject | RE: st: Strange Behaviour When Selecting Levels For Factor Variables In Regression With i# |
| Date | Tue, 22 Jan 2013 17:52:09 -0500 |
You need to tell the people who control these things that you can't be expected to work under such primitive and inhumane conditions. Barring that, I guess you need to use the i. or ib#. notation.
I'd be a little nervous if you aren't updated at least through 05aug2011 as there was an esoteric bug that could conceivably cause data corruption in some cases.
At 12:17 PM 1/22/2013, Sarah Edgington wrote:
Just wanted to quickly revisit this.
Now that I'm back at a computer with Stata 12 after being away for the
weekend, I can address it a bit more concretely.
Richard's output is exactly what I would expect to see. My output looks
different from Richard's and I suspect Daniel's did too. (Highlighting the
importance of including output, not just the syntax entered).
I'm going to guess this is an issue with Stata not being fully up-to-date
rather than it being a corrupt install issue. I get the same results across
two computers (one of which is not attached to any network and Stata was
installed on the two machines at different times). One has a non-updated
version of Stata 12 and one has the Aug 8, 2012 update. (Yes, in an ideal
world both computers would be completely updated; but since we don't have
admin rights on our own machines I'm sort of at the mercy of other people
for whom Stata updates are not the highest priority.)
As an aside, if I use the ib1.sex and ib0.sex syntax, I get the results I'd
expect (that is, the results Richard posted).
Here's what the regressions look like for me:
. regress bp i.sex i.when c.patient i.when#c.patient
Source | SS df MS Number of obs =
240
-------------+------------------------------ F( 4, 235) =
21.29
Model | 10881.7115 4 2720.42787 Prob > F =
0.0000
Residual | 30031.0843 235 127.791848 R-squared =
0.2660
-------------+------------------------------ Adj R-squared =
0.2535
Total | 40912.7958 239 171.183246 Root MSE =
11.305
----------------------------------------------------------------------------
----
bp | Coef. Std. Err. t P>|t| [95% Conf.
Interval]
---------------+------------------------------------------------------------
----
1.sex | -24.86705 2.919115 -8.52 0.000 -30.61803
-19.11608
2.when | -4.519608 2.937149 -1.54 0.125 -10.30611
1.266899
patient | .3029286 .0471077 6.43 0.000 .2101214
.3957359
|
when#c.patient |
2 | -.0094555 .0421309 -0.22 0.823 -.092458
.0735469
|
_cons | 150.5563 2.20753 68.20 0.000 146.2073
154.9054
----------------------------------------------------------------------------
----
. regress bp i1.sex i.when c.patient i.when#c.patient
Source | SS df MS Number of obs =
240
-------------+------------------------------ F( 4, 235) =
0.00
Model | 0 4 0 Prob > F =
1.0000
Residual | 40912.7958 235 174.097004 R-squared =
0.0000
-------------+------------------------------ Adj R-squared =
-0.0170
Total | 40912.7958 239 171.183246 Root MSE =
13.195
----------------------------------------------------------------------------
----
bp | Coef. Std. Err. t P>|t| [95% Conf.
Interval]
---------------+------------------------------------------------------------
----
1.sex | -108.1599 7.189742 -15.04 0.000 -122.3245
-93.99531
2.when | -87.68457 6.504943 -13.48 0.000 -100.5
-74.86912
patient | .6568478 .0562303 11.68 0.000 .5460678
.7676277
|
when#c.patient |
2 | 1.365172 .1037678 13.16 0.000 1.160738
1.569606
|
_cons | 170.7907 2.593321 65.86 0.000 165.6815
175.8998
----------------------------------------------------------------------------
----
. regress bp i0.sex i.when c.patient i.when#c.patient
note: 2.when#c.patient omitted because of collinearity
Source | SS df MS Number of obs =
240
-------------+------------------------------ F( 3, 236) =
28.48
Model | 10875.2747 3 3625.09155 Prob > F =
0.0000
Residual | 30037.5212 236 127.277632 R-squared =
0.2658
-------------+------------------------------ Adj R-squared =
0.2565
Total | 40912.7958 239 171.183246 Root MSE =
11.282
----------------------------------------------------------------------------
----
bp | Coef. Std. Err. t P>|t| [95% Conf.
Interval]
---------------+------------------------------------------------------------
----
0.sex | 24.86705 2.913236 8.54 0.000 19.12778
30.60632
2.when | -5.091667 1.456466 -3.50 0.001 -7.961003
-2.222331
patient | .2982009 .0420504 7.09 0.000 .2153588
.381043
|
when#c.patient |
2 | 0 (omitted)
|
_cons | 125.9753 4.009148 31.42 0.000 118.077
133.8736
----------------------------------------------------------------------------
----
-----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu
[mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Richard Williams
Sent: Friday, January 18, 2013 10:48 PM
To: statalist@hsphsun2.harvard.edu; statalist@hsphsun2.harvard.edu
Subject: Re: st: Strange Behaviour When Selecting Levels For Factor
Variables In Regression With i#
At 06:45 PM 1/18/2013, daniel56061-stata@yahoo.de wrote:
>Hello,
>
>when i use indicator i with selecting level of a factor variable like
>i1.varname to run a regression I get strange results.
>
>For example:
>
>sysuse blong,clear
>regress bp i.sex i.when c.patient i.when#c.patient
>regress bp i1.sex i.when c.patient i.when#c.patient
>regress bp i0.sex i.when c.patient i.when#c.patient
>
>This regression is wihout sense but theoretically it should estimate
>the same model and should give same results except for variable sex
>cause all I do is demand an indicator for a different level of a
>2-level variable sex.
>But if I run these lines I get three regressions with three different
>coefficients for the variable "when" and "patient" even I didnt change
>anything that should be related to these variables.
>Whats wrong here?
>
>regards
>Daniel
First off, I think you mean bplong.
Second, it seems to work fine for me. Are you leaving something out?
Could your version of Stata be corrupted or out of date? I'm sure the
problem is at your end because everything seems ok on mine. I'll just go
ahead and give all the output below.
. sysuse bplong.dta, clear
(fictional blood-pressure data)
. regress bp i.sex i.when c.patient i.when#c.patient
Source | SS df MS Number of obs =
240
-------------+------------------------------ F( 4, 235) =
21.29
Model | 10881.7115 4 2720.42787 Prob > F =
0.0000
Residual | 30031.0843 235 127.791848 R-squared =
0.2660
-------------+------------------------------ Adj R-squared =
0.2535
Total | 40912.7958 239 171.183246 Root MSE =
11.305
----------------------------------------------------------------------------
----
bp | Coef. Std. Err. t P>|t| [95%
Conf. Interval]
---------------+--------------------------------------------------------
---------------+--------
1.sex
| -24.86705 2.919115 -8.52 0.000 -30.61803 -19.11608
2.when
| -4.519608 2.937149 -1.54 0.125 -10.30611 1.266899
patient
| .3029286 .0471077 6.43 0.000 .2101214 .3957359
|
when#c.patient |
2 | -.0094555 .0421309 -0.22 0.823 -.092458
.0735469
|
_cons
| 150.5563 2.20753 68.20 0.000 146.2073 154.9054
----------------------------------------------------------------------------
----
. regress bp i1.sex i.when c.patient i.when#c.patient
Source | SS df MS Number of obs =
240
-------------+------------------------------ F( 4, 235) =
21.29
Model | 10881.7115 4 2720.42787 Prob > F =
0.0000
Residual | 30031.0843 235 127.791848 R-squared =
0.2660
-------------+------------------------------ Adj R-squared =
0.2535
Total | 40912.7958 239 171.183246 Root MSE =
11.305
----------------------------------------------------------------------------
----
bp | Coef. Std. Err. t P>|t| [95%
Conf. Interval]
---------------+--------------------------------------------------------
---------------+--------
1.sex
| -24.86705 2.919115 -8.52 0.000 -30.61803 -19.11608
2.when
| -4.519608 2.937149 -1.54 0.125 -10.30611 1.266899
patient
| .3029286 .0471077 6.43 0.000 .2101214 .3957359
|
when#c.patient |
2 | -.0094555 .0421309 -0.22 0.823 -.092458
.0735469
|
_cons
| 150.5563 2.20753 68.20 0.000 146.2073 154.9054
----------------------------------------------------------------------------
----
. regress bp i0.sex i.when c.patient i.when#c.patient
Source | SS df MS Number of obs =
240
-------------+------------------------------ F( 4, 235) =
21.29
Model | 10881.7115 4 2720.42787 Prob > F =
0.0000
Residual | 30031.0843 235 127.791848 R-squared =
0.2660
-------------+------------------------------ Adj R-squared =
0.2535
Total | 40912.7958 239 171.183246 Root MSE =
11.305
----------------------------------------------------------------------------
----
bp | Coef. Std. Err. t P>|t| [95%
Conf. Interval]
---------------+--------------------------------------------------------
---------------+--------
0.sex
| 24.86705 2.919115 8.52 0.000 19.11608 30.61803
2.when
| -4.519608 2.937149 -1.54 0.125 -10.30611 1.266899
patient
| .3029286 .0471077 6.43 0.000 .2101214 .3957359
|
when#c.patient |
2 | -.0094555 .0421309 -0.22 0.823 -.092458
.0735469
|
_cons
| 125.6893 4.214552 29.82 0.000 117.3862 133.9924
----------------------------------------------------------------------------
----
.
-------------------------------------------
Richard Williams, Notre Dame Dept of Sociology
OFFICE: (574)631-6668, (574)631-6463
HOME: (574)289-5227
EMAIL: Richard.A.Williams.5@ND.Edu
WWW: http://www.nd.edu/~rwilliam
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------------------------------------------- Richard Williams, Notre Dame Dept of Sociology OFFICE: (574)631-6668, (574)631-6463 HOME: (574)289-5227 EMAIL: Richard.A.Williams.5@ND.Edu WWW: http://www.nd.edu/~rwilliam * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/faqs/resources/statalist-faq/ * http://www.ats.ucla.edu/stat/stata/