LISTSERV at the University of Georgia
Menubar Imagemap
Home Browse Manage Request Manuals Register
Previous messageNext messagePrevious in topicNext in topicPrevious by same authorNext by same authorPrevious page (July 2004)Back to main SPSSX-L pageJoin or leave SPSSX-L (or change settings)ReplyPost a new messageSearchProportional fontNon-proportional font
Date:         Thu, 15 Jul 2004 22:42:55 -0400
Reply-To:     "Edmund J. Bini, M.D., M.P.H." <liver.doc@verizon.net>
Sender:       "SPSSX(r) Discussion" <SPSSX-L@LISTSERV.UGA.EDU>
From:         "Edmund J. Bini, M.D., M.P.H." <liver.doc@verizon.net>
Subject:      Re: Odds Ratios and Proportions
Comments: To: paulandpen@optusnet.com.au
In-Reply-To:  <200407160229.i6G2TAk02299@mail022.syd.optusnet.com.au>
Content-Type: text/plain; charset="us-ascii"

Thanks Paul. I understand the part about OR overestimating RR when the outcome is common. Logistic regression is often used even if the outcome is common in order to adjust for potential confounders but people have to accept odds ratios for what they are - odds ratios - and not try to convert them to a RR. Do others feel the logistic regression should not be used if the outcome is > 10%? The part I was confused about is when they asked us to convert the OR from logistic regression to a proportion. Maybe I am reading too deep into this and they just want us to abandon the use of logistic regression and just present out data unadjusted as percentages.

-----Original Message----- From: paulandpen@optusnet.com.au [mailto:paulandpen@optusnet.com.au] Sent: Thursday, July 15, 2004 10:29 PM To: Edmund J. Bini, M.D., M.P.H. Cc: SPSSX-L@LISTSERV.UGA.EDU Subject: Re: Odds Ratios and Proportions

Hi there Edmund

'However, as both the prevalence and OR increase, the error in the approximation quickly becomes unacceptable: if the baseline prevalence is 10% an OR of 4 is equivalent to a RR of 3, a discrepancy of 25%'

Source http://www.jr2.ox.ac.uk/bandolier/band25/b25-6.html.

Regards Paul

> Edmund J. Bini, M.D., M.P.H. <liver.doc@verizon.net> wrote: > > I sent this last week but am not sure if it was delivered. I apologize > if it > is a duplicate e-mail. Can someone please help me address the issue > below > using SPSS? > > > > I recently submitted a paper to a journal describing a randomized > controlled > study we did to increase compliance with colon cancer screening and > have a > statistical question about one of the comments we received when the > paper > was reviewed. We randomly allocated 788 patients to receive an > intervention > or standard of care and looked at compliance with screening at 6 months > after the intervention. By 6 months, 65.9% of patients in the > intervention > group completed the screening test compared with 51.3% in the standard > of > care group (p < 0.001). We then did multivariable logistic regression > to > determine if our intervention was significantly associated with > compliance > after adjusting for several potential confounding variables. The > adjusted > relative odds of compliance was 1.9 (95% CI, 1.4 - 2.6) comparing the > intervention to the standard of care group. > > > > One of the associate editors of the journal made the statement below > and I > am interested in your comments about this as well as any information > about > how to convert odds ratios from logistic regression to proportions in > SPSS. > Is this possible or logical? Any help or link to a reference about this > would be very much appreciated. > > > > Given that your outcome of interest was relatively common, we are > concerned > that this may > > violate the assumptions of logistic regression. Specifically, in order > to > avoid overstating the prevalence ratio (which the odds ratio is > intended to > approximate), the outcome of interest > > needs to occur <=10% of the time. It is more accurate to convert the > odds > ratios into proportions when the outcome is more frequent than that. > > > > Thanks! > > Ed > >


Back to: Top of message | Previous page | Main SPSSX-L page