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From |
Lee Savage <leemsavage@yahoo.co.uk> |

To |
"statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu> |

Subject |
Re: st: Large standard error, Cox PH |

Date |
Sat, 28 Jul 2012 13:48:12 +0100 (BST) |

The study is an analysis of government termination, estimated using a Cox proportional hazards model. The problem variable is 'Minority', this is a binary variable that indicates whether or not a government holds a parliamentary majority. The problem is that the standard error of the coefficient is extremely high. I have only seen this before when the coefficient was insignificant but in this case the coefficient is significant (as you can see below). Multicollinearity isn't a problem. I'm looking for advice on whether or not this is a problem or can I simply report the model and just state that the high SE of the 'Minority' variable means that it can't really be generalized? Here is the printout. Iteration 0: log pseudolikelihood = -40.288812 Iteration 1: log pseudolikelihood = -28.304301 Iteration 2: log pseudolikelihood = -26.968036 Iteration 3: log pseudolikelihood = -26.902024 Iteration 4: log pseudolikelihood = -26.901788 Refining estimates: Iteration 0: log pseudolikelihood = -26.901788 Cox regression -- Breslow method for ties No. of subjects = 19 Number of obs = 347 No. of failures = 19 Time at risk = 347 Wald chi2(7) = 1603.76 Log pseudolikelihood = -26.901788 Prob > chi2 = 0.0000 Haz. Robust Ratio SE z P>z [95% Conf.Interval] Minority 77.01 56.61 5.91 0.00 18.23 325.28 Ideology 0.84 0.20 -0.73 0.47 0.52 1.35 formdays 0.94 0.03 -2.16 0.03 0.90 0.99 nogovtpart~s 1.51 1.68 0.37 0.71 0.17 13.34 ciep12 1.36 1.25 0.34 0.74 0.23 8.21 ConsNoCon 1.28 1.18 0.27 0.79 0.21 7.86 tvc Unemployment 0.99 0.01 -2.31 0.02 0.98 1.00 GDP 1.00 0.00 2.24 0.03 1.00 1.00 Inflation 0.98 0.01 -4.38 0.00 0.97 0.99 __________________________ From: Steve Samuels <sjsamuels@gmail.com> To: statalist@hsphsun2.harvard.edu Sent: Friday, 27 July 2012, 21:30 Subject: Re: st: Large standard error, Cox PH To answer your questions, we'd need more detail. Describe the study and the problem variable in particular. As the FAQ request, "Say exactly what you typed and exactly what Stata typed (or did) in response". Steve sjsamuels@gmail.com On Jul 27, 2012, at 2:20 PM, Lee Savage wrote: I have estimated a Cox PH model using a small sample (n=19, 347 months at risk). For one of my covariates I have found a large hazard ratio (77.01) with a correspondingly large standard error (56.61). I have seen this before but every time the covariate was insignificant, in the current model the covariate is significant (p=.001). I have tested the covariates for collinearity and everything looks fine. I think the probable cause is the small sample size. So my question is: is this a problem for my model overall model? My inclination is to report the model as it is and just state that the significant effect for the covariate in question should be treated with extreme caution, perhaps even ignored. I'd appreciate any advice on this. Thanks. * * 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: Large standard error, Cox PH***From:*Steve Samuels <sjsamuels@gmail.com>

**Re: st: Large standard error, Cox PH***From:*Steve Samuels <sjsamuels@gmail.com>

**References**:**st: Large standard error, Cox PH***From:*Lee Savage <leemsavage@yahoo.co.uk>

**Re: st: Large standard error, Cox PH***From:*Steve Samuels <sjsamuels@gmail.com>

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