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From |
"Sebastian E. Wenz" <[email protected]> |

To |
[email protected] |

Subject |
Re: st: RE: missing std. errors |

Date |
Thu, 21 Aug 2008 01:47:00 +0200 |

Richard A. Forshee suggested the following as a solution to Nishant's problem (see the end of this e-mail for the problem): "Have you excluded a reference category? If not, your dummy variables will be perfectly collinear with the constant." It is a good idea to pick a reference category by yourself---(i) you might wanna look at point estimates of the dummies in comparison to a specific group; (ii) you might wanna pick a category that ensures "stable results", put differently: pick a category of reasonable size (=a group that is not too small). However, excluding a reference category is not the solution to Nishant's problem as I see it; Stata automatically drops variables that show very high collinearity. Actually, Nishant's output looks like this is what happened: "dummy10" is reported as "(dropped)". As far as I read Nishant's output, the problem is likely to be linked to the usage of the -cluster()- option. I am inferring from the output, since Nishant is not reporting the code he typed. Actually, I have no idea what the problem is exactly, but Nishant should check the relations among the cluster-variable "familyid", the dummies ("dummy1"-"dummy10"), and the dependent variable on collinearities, nested structures, and group/cell sizes. Hope this helps (somewhat), Sebastian > First of all, I am using Stata/SE 10.0 on Windows. > > My question is about missing standard errors. I am implementing a > simple linear regression model with roughly 50 indicator/dummy variables > on the right-hand side (besides a dozen other independent variables), > and in the results generated, standard errors for the coefficients of > all the dummy variables are not reported. In addition, the standard > error for the constant term is also not reported. > > I thought it might be due to the skewed distribution of my observations > across the 50 categories (represented by the 50 indicator/dummy > variables), i.e., it might be that there are too many 1's or 0's in some > of the categories. So I tried reducing the number of indicator/dummy > variables by using much more coarsely-defined categories. This coarse > categorization brings down the number of indicator/dummy variables to > 10, but I still get the same problem! (Attached below is part of the > output generated.) > > Any help would be much appreciated. > > Thanks, > > Nishant > > > P.S. Here's a sample of what I see (using 10 indicator variables) in > the output generated by Stata: > > Linear regression Number of obs = > 226223 > F( 58, 454) = > . > Prob > F = > . > R-squared = > 0.0750 > Root MSE = > .02272 > > (Std. Err. adjusted for 455 clusters in > familyid) > ------------------------------------------------------------------------ > ------ > | Robust > familyport~1 | Coef. Std. Err. t P>|t| [95% Conf. > Interval] > -------------+---------------------------------------------------------- > ------ > indvar1 | .0002341 .0001428 1.64 0.102 -.0000465 > .0005147 > > ... > > indvar14 | .0002029 .0005647 0.36 0.720 -.0009069 > .0013127 > dummy1 | -.0041449 . . . . > . > dummy2 | -.0039503 . . . . > . > dummy3 | -.0038193 . . . . > . > dummy4 | -.003429 . . . . > . > dummy5 | -.0034715 . . . . > . > dummy6 | -.003175 . . . . > . > dummy7 | -.0033819 . . . . > . > dummy8 | -.002303 . . . . > . > dummy9 | -.0022382 . . . . > . > dummy10 | (dropped) > _cons | .0790628 . . . . > . > ------------------------------------------------------------------------ > ------ > > . > > > > > > > > * > * For searches and help try: > * http://www.stata.com/help.cgi?search > * http://www.stata.com/support/statalist/faq > * http://www.ats.ucla.edu/stat/stata/ > > * > * For searches and help try: > * http://www.stata.com/help.cgi?search > * http://www.stata.com/support/statalist/faq > * http://www.ats.ucla.edu/stat/stata/ > * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**Follow-Ups**:**Re: st: RE: missing std. errors***From:*Nishant Dass <[email protected]>

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