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

From |
VISINTAINER PAUL <VISINT@NYMC.EDU> |

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

Subject |
st: RE: Groups (qantiles) in Hosmer-Lemeshows goodness of fit test |

Date |
Thu, 13 Jun 2002 12:21:14 -0400 |

You can do this easily. Run your model .logistic dead crib .predict phat ----> this gives you the probability of "dead" .predict xb, xb ----> this is the linear predictor, e.g., the solution of your regression equation .sort phat ----> this sorts the dataset from lowest to highest phat values, to correspond with the H-L table .list crib xb phat The H-L table divides the dataset into percentiles of pr(dead) from lowest to highest. The -list- command will associate each "crib" value with its linear predictor, xb and its predicted probability, phat. The H-L cutpoints will correspond to the phat listing. paul Paul F. Visintainer, PhD School of Public Health New York Medical College Valhalla, NY 10595 (914) 594-4804 (phone) (914) 594-4292 (fax) -----Original Message----- From: Kaaresen Per Ivar [mailto:per.ivar.kaaresen@rito.no] Sent: Wednesday, June 12, 2002 9:08 AM To: 'statalist@hsphsun2.harvard.edu' Subject: st: Groups (qantiles) in Hosmer-Lemeshows goodness of fit test Ikke sensitiv - ignore message - due to in-house security Dear friends Could anybody help me with this (again) probably rather simple problem. I'm working with this CRIB (clinical risk index for babies) ability to predict hospital death in a population (not individual) level. To test the calibration of the score I've done a logistic regression and then a Hosmer-Lemesow goodness of fit test. The variables are dead and crib (range 0-21, integers only). . logit dead crib Iteration 0: log likelihood = -206.16559 Iteration 1: log likelihood = -155.91351 Iteration 2: log likelihood = -150.13801 Iteration 3: log likelihood = -150.00793 Iteration 4: log likelihood = -150.00765 Logit estimates Number of obs = 443 LR chi2(1) = 112.32 Prob > chi2 = 0.0000 Log likelihood = -150.00765 Pseudo R2 = 0.2724 ---------------------------------------------------------------------------- -- dead | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+-------------------------------------------------------------- -- crib | .3516896 .0414307 8.49 0.000 .2704869 .4328923 _cons | -4.086216 .3701967 -11.04 0.000 -4.811788 -3.360644 ---------------------------------------------------------------------------- -- . lfit,group(10) table Logistic model for dead, goodness-of-fit test (Table collapsed on quantiles of estimated probabilities) note: because of ties, there are only 9 distinct quantiles _Group _Prob _Obs_1 _Exp_1 _Obs_0 _Exp_0 _Total 1 0.0233 2 1.8 74 74.2 76 3 0.0328 2 2.2 65 64.8 67 4 0.0642 3 3.7 60 59.3 63 5 0.0888 2 3.2 34 32.8 36 6 0.1217 4 2.9 20 21.1 24 7 0.2188 15 13.7 56 57.3 71 8 0.2848 10 9.7 24 24.3 34 9 0.4458 12 12.4 20 19.6 32 10 0.9644 28 28.4 12 11.6 40 number of observations = 443 number of groups = 9 Hosmer-Lemeshow chi2(7) = 1.34 Prob > chi2 = 0.9874 My question is (yes, I see the possible problem with small numbers in 5 of the cells - but that's not the question now): How can I find the intervals in CRIB score which the different _Group (qantiles) represent? I would like to present the results something like: CRIB _Prob _Obs_1 _Exp_1 _Obs_0 _Exp_0 _Total 0-1 0.0233 2 1.8 74 74.2 76 2-4 0.0328 2 2.2 65 64.8 67 5-7 0.0642 3 3.7 60 59.3 63 . 0.0888 2 3.2 34 32.8 36 . 0.1217 4 2.9 20 21.1 24 . 0.2188 15 13.7 56 57.3 71 . 0.2848 10 9.7 24 24.3 34 . 0.4458 12 12.4 20 19.6 32 . 0.9644 28 28.4 12 11.6 40 I've seen this kind of presentation in different papers - and would be very thankful if somebody could explain how I can do this in Stata. Regards Per Ivar Kaaresen MD University Hospital Nothern Norway * * 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/ * * 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/

- Prev by Date:
**st: RE: Re: Tab and Matcell** - Next by Date:
**st: Formatting variables** - Previous by thread:
**st: RE: RE: Bootstrap Commands - References** - Next by thread:
**st: Formatting variables** - Index(es):

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