[Date Prev][Date Next][Thread Prev][Thread Next][Date index][Thread index]

From |
sara borelli <saraborelli77@yahoo.it> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: cluster and F test |

Date |
Mon, 7 Jul 2008 08:13:00 +0000 (GMT) |

Austin, thank you very much for your help, Sara --- Dom 6/7/08, Austin Nichols <austinnichols@gmail.com> ha scritto: > Da: Austin Nichols <austinnichols@gmail.com> > Oggetto: Re: st: cluster and F test > A: statalist@hsphsun2.harvard.edu > Data: Domenica 6 luglio 2008, 16:05 > sara borelli <saraborelli77@yahoo.it> : > An individual SE may be OK, in the sense that a test > involving only > one coef may have approximately the right size, but e(V) > has rank M-1 > and so the upper limit on the number of coefs that can > included in one > joint test is M-1. The reported SEs ignore the cov between > the 37 > estimates; they offer a test of one coef each, ignoring the > fact that > you can't actually test all 37, or even 14, jointly. > But in this > case, a test of even one coef is suspect, because you have > M-1=13 > which is a very small number to consider close to infinity. > 50 > clusters, or at the very least 20 large balanced clusters, > are needed > to be reasonably sure the size distortion is not too large. > In > general, it probably seems like a bad idea to include more > variables > than you have effective df, though for the CRSE, Stata will > let you do > it, for various reasons. For example, if you had 50 > clusters, 50 > fixed effects for cluster and 120 fixed effects for time, > you could > include these 170 effects as 168 dummy variables along with > one > explanatory variable of interest. You can never test the > joint sig of > the cluster FE nor the joint sig of the time FE, and you > will (one > hopes) not be testing smaller groups of these FE either, so > the only > test you plan to do in this case is on the one explanatory > variable of > interest, with 49 df. In this case, you should be fine. > Note the > relevant number is M-k, number of clusters less number of > constraints. > > --Austin > > On Sun, Jul 6, 2008 at 5:14 AM, sara borelli > <saraborelli77@yahoo.it> wrote: > > Hi [Austin], > > thank you very much for your help. > > > > When I test (with the F-test) 18 restrictions with 14 > clusters stata drops the 5 constraints because, as you > said, it can test only 13 constraints. > > There is something I do not understand, however. With > the cluster option the number of observations useful to > estimate the standard errors becomes the number of > clusters, 14. Thus, if I have 37 standard errors to > estimate and only 14 clusters, how is that possible that > stata is able to estimate all the standar errors, but still > test only 13 constraints? > > Basically, when the number of clusters is smaller than > the number of regressors, is only the F-test computed in a > wrong way or also the standar errors? > > I am sorry to keep usking about this, but I ma a bit > confused > > Thank you > > Sara > > > > --- Sab 5/7/08, Austin Nichols > <austinnichols@gmail.com> ha scritto: > > > >> Da: Austin Nichols <austinnichols@gmail.com> > >> Oggetto: Re: st: cluster and F test > >> A: statalist@hsphsun2.harvard.edu > >> Data: Sabato 5 luglio 2008, 19:01 > >> sara borelli <saraborelli77@yahoo.it>: > >> The cluster-robust standard error (CRSE) estimator > has at > >> most M-1 df > >> with M clusters, so with 14 clusters you can test > the joint > >> sig. of at > >> most 13 coefs. But the performance of the > estimator gets > >> worse as you > >> increase the the number of constraints. The > CRSE's > >> performance > >> improves as M-k increases toward infinity, where M > is the > >> number of > >> clusters and k the number of constraints you are > testing, > >> and for M-k > >> at least 20 and clusters balanced you should > expect good > >> performance. > >> Since you have M-k equal to one (the minimum > possible > >> value), you > >> should expect that the estimated variance is too > low and > >> the F stat is > >> too high, on average. Note that clusters are like > >> super-observations, > >> for the purposes of the SE of estimated coefs, so > a > >> regression on 37 > >> variables with 14 clusters is a bit like a > regression on 37 > >> vars with > >> 14 obs--you really don't want to test more > than one > >> coef there, and > >> maybe not even that many. How are your clusters > defined? > >> Is there > >> any possibility of adding more clusters, or > redefining them > >> sensibly > >> so you have more clusters? > >> > >> On Fri, Jul 4, 2008 at 5:16 AM, sara borelli > >> <saraborelli77@yahoo.it> wrote: > >> > Dear Stata List members, > >> > > >> > I have found some related questions on FAQs, > but I > >> cannot fins exactly what I need. > >> > I am running a regression with the cluster > option. I > >> have 37 independent variables (including the > constant), > >> 1647 observations, and 14 clusters. > >> > I want to test the joint significance of 18 > variables. > >> > If I do NOT use the cluster option the F is > calculated > >> correctly as F(18, 1637). > >> > But once I introduce the cluster option I get > the > >> following result: > >> > (1) x1= 0 > >> > (2) x2 = 0 > >> > (3) x3 = 0 > >> > (4) x3 = 0 > >> > ... > >> > (18) x18 = 0 > >> > Constraint 1 dropped > >> > Constraint 2 dropped > >> > Constraint 3 dropped > >> > Constraint 4 dropped > >> > Constraint 14 dropped > >> > > >> > F( 13, 13) = 109.42 > >> > Prob > F = 0.0000 > >> > > >> > I guess stata is doing something on the > degree of > >> freedoms, but I have not clear what is going on, > why it is > >> dropping the constraints. Is the final F test > calculated > >> correct? > >> > Thank you in advance for any help > * > * For searches and help try: > * http://www.stata.com/support/faqs/res/findit.html > * http://www.stata.com/support/statalist/faq > * http://www.ats.ucla.edu/stat/stata/ Posta, news, sport, oroscopo: tutto in una sola pagina. Crea l'home page che piace a te! www.yahoo.it/latuapagina * * For searches and help try: * http://www.stata.com/support/faqs/res/findit.html * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**Follow-Ups**:**Re: st: cluster and F test***From:*"Ángel Rodríguez Laso" <angelrlaso@gmail.com>

**References**:**Re: st: cluster and F test***From:*"Austin Nichols" <austinnichols@gmail.com>

- Prev by Date:
**Re: st: keeping inventory while cleaning data** - Next by Date:
**st: Estimating total factor productivity** - Previous by thread:
**Re: st: cluster and F test** - Next by thread:
**Re: st: cluster and F test** - Index(es):

© Copyright 1996–2016 StataCorp LP | Terms of use | Privacy | Contact us | What's new | Site index |