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From |
Jeph Herrin <junk@spandrel.net> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
st: predict after -streg- |

Date |
Tue, 10 Jul 2007 13:07:56 -0400 |

This is either a Stata question or a stats question, apologies if it turns out to be the latter. I am using -streg- to estimate a parametric survival model with a lognormal distribution. The data represent readmissions to hospital after a discharge, with readmission being considered a failure. All patients (n=424,787) are followed for 30 days, with approximately 25% readmitted within that time. -> stset ftime, failure(radm) failure event: radm != 0 & radm < . obs. time interval: (0, ftime] exit on or before: failure ------------------------------------------------------------------------------ 424787 total obs. 0 exclusions ------------------------------------------------------------------------------ 424787 obs. remaining, representing 95529 failures in single record/single failure data 1.07e+07 total analysis time at risk, at risk from t = 0 earliest observed entry t = 0 last observed exit t = 30 My model has 30+ covariates representing demographic and comorbid characteristics of the patients. I would like to get a predicted time to readmission for each patient in the cohort. I will need to specify shared frailty by hospital but for now am working with a standard model. What is bothering me is that while 95,000 patients are acutally readmitted prior to 30 days, when I calculate the predicted time to failure: . predict median, median time . gen prd30 = median<=30 . count if prd30 30 Why the huge difference? Diagnostics show the lognormal model fitting quite well, with the residuals falling right along where they should. Either I don't understand what the model is doing, or I'm not calculating the correct predicted value. Should I expect this? Thanks in advance for any insights. Jeph * * 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/

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