I've sent this once before but it got 'spammed' - so here is
another go as it may be of general interest.
Ref to
Samia
Alhabib
I'm afraid you've illustrated why it is difficult to explain
what an odds ratio is and that it's meaning is
context-sensitive.
Using your example, if we consider rates of diabetes in 200
males and 200 females, and we keep the odds ratio at 4.5 (as
close as I could get to 4.5), you will see that as the odds
of diabetes increase in each group the ratio of
males/females with diabetes becomes smaller, making the
explanation "male is 4.5 times more likely to have diabetes
than female" increasingly incorrect.
Your explanation would be correct if you were talking about
risk ratios (which are context-insensitive), but not odds
ratios.
MALE FEMALE OR MALE/FEMALE
17/183 4/196 4.55 4.25
32/168 8/192 4.57 4
56/144 16/184 4.47 3.5
72/128 22/178 4.55 3.27
90/110 30/170 4.51 2.9
On Sun, 5 Feb 2012 08:10:18 -0800
s alhabib <
[log in to unmask]>
wrote:
> Dear Simon:
>
> An Odd ratio of 4.5, for example, in explaining the
risk of developing diabetes in male than female is to say:
male is 4.5 times more likely to have diabetes than female
if they did not
excercise...this
is an a virtual example and does not imply any sort of
evidence,
>
>
Samia
>
> Dr.
Samia
Alhabib, MD,
MSc
PHC, PG-Dip
EBHC
> Research Associate
> Academic Unit of Primary health Care
> Faculty of Medicine
> University of Bristol,
> Barley House,
Oakfield
Grove
> Bristol, BS8 2
BN
> UK
>
>
> ________________________________
> From: Simon
Hatcher
<
[log in to unmask]>
> To:
[log in to unmask]
Sent: Sunday, 5 February 2012, 15:35
> Subject: Re: Odds ratios explained
>
> In a previous post on this list someone asked the
question "how do you explain odds ratios to patients?" -
which from memory no one ever answered. I understand odds
ratios and I can draw 2x2 tables with the best of them
however how do you include odds ratios in conversations with
patients - in simple language what do odds ratios mean for
patients?
>
> Cheers
>
> Simon
>
> Associate Professor Simon
Hatcher
> Department of Psychological Medicine
> Faculty of Medical and Health Sciences
> The University of Auckland
> New
Zealand
>
>
> ________________________________________
> From: Evidence based health (
EBH) [
[log in to unmask]]
on behalf of k.
hopayian
[
[log in to unmask]]
> Sent: Monday, 6 February 2012 12:52 a.m.
> To:
[log in to unmask]
> Subject: Re: Odds ratios explained
>
> I am interested to know if the explanation below is any
better than
Wikipedia,
it is the one I use with students and trainees.
> Dr Kev (
Kevork)
Hopayian, MD
FRCGP
> Hon Sen Lecturer
> Norwich Medical School
> University of East Anglia
> Norwich
> NR4 7
TJ
> Making your
practice
evidence-based
http://www.rcgp.org.uk/bookshop
>
> The odds of something happening is the ratio of the
probability of it happening to the probability of it not
happening.
> Let probability of an event = p
(NB p is a proportion between 0 and 1)
> Then the probability of an event not happening = 1–p
> So odds = p/(1–p)
> (In racing, odds are usually given as the odds against
something happening but we are dealing here with more lofty
matters than the 2.15 at Epsom).
> The odds ratio for two groups is simply the ratio of
their odds.
>
>
> Disorder present
>
> Disorder absent
>
> Exposed group
>
> a
>
> b
>
> Comparison group
>
> c
>
> d
>
>
> Look at the 2X2 table and see if you can follow this:
> p in exposed group = a/(a+b)
> Probability of event not happening in exposed group
> = 1–p = 1– a/(a+b) = b/(a+b)
> Odds in exposed group
> = { a/(a+b)}/{ b/(a+b)}= a/b
> Similarly, odds in control group
> = c/d
> So OR = {a/b}/{c/d} = ad/
bc
> If draw a line between the cells that multiply each
other in the 2X2 table (a to d and b to c), you may see why
some people call the OR the cross test.
> Three important things you need to know about
ORs to get by in life
without learning the calculation:
>
> * An OR <1 means that fewer things happen in the
exposed group than the comparison group (good when the thing
is bad, e.g. a fall). An OR >1 means that more things
happen in the exposed group than the comparison group
(good when the thing is good, e.g. post-op pain relief, bad
when the thing is bad, e.g.
osteoporotic fracture). An OR =1 means
no difference.
> *
ORs
are not intuitive, e.g., OR = 2 does not mean the risk is
doubled, it is not the same as RR (relative risk) = 2
except…
> * …when the frequency of events (risk, event rate)
is low, then OR is approximately the same as RR.
>
>
>
>
>
> On 5 Feb 2012, at 10:51, Jane Hartley wrote:
>
> Can anyone suggest an easy guide to odds ratios and
other basic stats functions?
>
> A clinical friend has asked for some help with a
dissertation and understanding source papers, this is not
her area of expertise and she has been frightened off by the
scholarly texts she has been directed too - I suspect her
supervisors are not in their area of comfort with this
either.
>
> I have moved professionally away from supporting
EBH and so am not up
to date with user friendly articles. Dare I admit that I
looked at the
wikipedia
which seemed comprehensive but impenetrable to the novice.
>
> suggestions very welcome
>
> Jane Hartley