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From |
"Carlo Lazzaro" <carlo.lazzaro@tin.it> |

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

Subject |
st: R: What is this problem called? |

Date |
Fri, 16 Nov 2007 10:07:47 +0100 |

Kieran wrote: Gidday, A colleague has asked me the following question: Suppose a surgeon performs a number of surgical procedures using a new technique. He/she records the operating time for each operation. How would the data be analysed so as to determine the number of procedures performed before the operating time stabilises? I haven't come across a problem quite like this before, but it seems to me that it's a question that might arise, for example, when evaluating the implementation of new industrial or manufacturing processes. I have an idea about how I would approach this analysis, but first I'd like to have a look at what others may have done. Searching the literature is difficult though if you don't know what the problem is called. Does anyone recognise this problem or something analogous to it and can you give me a name I can search on or point me to a few relevant papers. I can back-track though the literature from there. Thanks in advance, Kieran ______________________________________________ Kieran McCaul MPH PhD WA Centre for Health & Ageing (M573) University of Western Australia Level 6, Ainslie House 48 Murray St Perth 6000 email: kamccaul@meddent.uwa.edu.au http://myprofile.cos.com/mccaul _______________________________________________ Dear Kieran, provided that I have understood well your question, I would suggest you the following example (supposing 20 patients undergoing a given surgical procedure and Operating_Time expressed in minutes and ordered in 4 Groups (five surgical procedures each) showing a decreasing Operating Time as the learning curve increases) (please, see below): ------------------------------begin example-------------------------------- set obs 20 gen Min_Op_Time=50 in 1/2 gen Min_Op_Time=55 in 3/5 replace Min_Op_Time=40 in 6/7 replace Min_Op_Time=45 in 8/10 replace Min_Op_Time=30 in 11/12 replace Min_Op_Time=35 in 13/15 replace Min_Op_Time=20 in 16/17 replace Min_Op_Time=35 in 13/15 replace Min_Op_Time=25 in 18/20 gen Group=1 if if Min_Op_Time==50 | Min_Op_Time==55 replace Group=2 if Min_Op_Time==40 | Min_Op_Time==45 replace Group=3 if Min_Op_Time==30 | Min_Op_Time==35 replace Group=4 if Min_Op_Time==20 | Min_Op_Time==25 oneway Min_Op_Time Group, bonferroni tabulate ------------------------------end example-------------------------------- You might also perform a Bootstrap ANOVA for sensitivity analysis purposes. HTH and Kind Regards, Carlo * * 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/

**References**:**st: What is this problem called?***From:*"Kieran McCaul" <kamccaul@meddent.uwa.edu.au>

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