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st: R: What is this problem called?


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


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