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From |
jverkuilen <jverkuilen@gc.cuny.edu> |

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

Subject |
RE: st: AW: gllamm (poisson) execution time |

Date |
Thu, 25 Jun 2009 10:27:49 -0400 |

My thoughts exactly.... -xtmepoisson- should be markedly more efficient than -gllamm- as it is optimized for this problem. -gllamm- is very flexible but this comes at a cost. -----Original Message----- From: "Martin Weiss" <martin.weiss1@gmx.de> To: statalist@hsphsun2.harvard.edu Sent: 6/24/2009 3:13 AM Subject: st: AW: gllamm (poisson) execution time <> Have you looked into -xtmepoisson-? HTH Martin -----Ursprüngliche Nachricht----- Von: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] Im Auftrag von Keith Dear (work) Gesendet: Mittwoch, 24. Juni 2009 08:01 An: statalist@hsphsun2.harvard.edu Cc: Ainslie Butler Betreff: st: gllamm (poisson) execution time We are trying to model daily mortality by poisson regression, over 17 years, by postcode, with postcode as a single random intercept term. In Stata10/MP4 on a linux cluster our models each take 7 or 8 hours to fit, which is too long to be feasible for exploratory analyses. The full dataset has >14 million rows of data: a row for every day for 1991-2007 for every postcode in Australia (~2200 postcodes), but to get things moving we are starting with smaller geographical regions of only 100 or 200 postcodes. Thus N=17*365*(100 or 200), about a half or one million. Also we are starting with failrly simple models, p=17 fixed-effect parameters just for trend and annual cycles. The models converge ok, eventually, in only a few iterations and with typical condition number about 2. I found this in the list archives (from Sophia Rabe-Hesketh in 2003): ==> biggest gain is to reduce M, followed by n, p and N Here we have M=1, n=5 (down from the default of 8), p=17, but N=6E5 or more. There does not seem to be much prospect of reducing any of those, indeed we will need to substantially increase p (for more interesting models) and N (to cover all of Australia at once). Is there hope? Are there alternatives to gllamm for this? Or are we overlooking something basic here? Keith -- Dr Keith Dear Senior Fellow National Centre for Epidemiology and Population Health ANU College of Medicine, Biology and Environment Building 62, cnr Mills and Eggleston Roads Australian National University Canberra ACT 0200 Australia T: 02 6125 4865 F: 02 6125 0740 M: 0424 450 396 W: nceph.anu.edu.au/Staff_Students/staff_pages/dear.php CRICOS provider #00120C http://canberragliding.org/ * * 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/

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