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[Sarah]

Hi all,

I am aware this is a very basic question, but wanted some assistance
with this. I calculating the Risk Difference, Risk Ratio, and Odds
Ratio for a table of data where people have recieved a vaccine or
placebo, and then whether they became infected with the disease or not
(2x2 table). How do I interpret each of the RR, RD, and OR
differently? At the minute all my interpretations say basically the
same thing, just with the different values calculated. Basically, what
is the difference between the risk ratio, and the odds ratio when
interpretating the results?

Also, does my table need to be in any specific order? I am aware I can
use computer packages to work these out, but for this bit of work I
need to do them by hand!

Thanks,

Sarah

[Steve Simon, P.Mean Consulting]

Sarah wrote:

> I am aware this is a very basic question, but wanted some assistance
> with this. I calculating the Risk Difference, Risk Ratio, and Odds
> Ratio for a table of data where people have recieved a vaccine or
> placebo, and then whether they became infected with the disease or not
> (2x2 table). How do I interpret each of the RR, RD, and OR
> differently? At the minute all my interpretations say basically the
> same thing, just with the different values calculated. Basically, what
> is the difference between the risk ratio, and the odds ratio when
> interpretating the results?

I'm talking about this very issue at a free webinar tomorrow, but you
can find all the important issues in my draft handout:

http://www.pmean.com/webinars/RiskMeasures.html

If the measures all say pretty much the same thing, then just choose one
based on what others working on similar sorts of problems use. The only
restriction is that you must use an odds ratio if you have a
case-control design, as the other measures are misleading in a design
like this that artificially controls the prevalence of the disease. It
doesn't sound like your data is from a case-control design, though.

I would suggest that the Number Needed to Treat is the best statistic to
use in this example, as it tells you how many people have to endure the
cost inconvenience, pain, and risk of vaccination in order to prevent
one extra disease on average. In one example cited above, a single case
of flu was prevented on average for every six people vaccinated. That
number makes it easy for you to assess the cost/benefit trade-offs of a
mass vaccination program.

> Also, does my table need to be in any specific order? I am aware I can
> use computer packages to work these out, but for this bit of work I
> need to do them by hand!

I offer some general advice about how to lay out data tables at

http://www.pmean.com/news/2009-09.html#3
http://www.childrens-mercy.org/stats/weblog2006/RoundingNumbers.asp
http://www.childrens-mercy.org/stats/model/percentage.asp

In general, I have found that placing the exposure or treatment
(vaccination in your case) as the rows and the outcome (disease in your
case) as the column works well along with the inclusion of row
percentages. That's a general rule though, and there are plenty of
exceptions. Try the table several different ways and see what gives the
clearest picture of your data.

Please be sure to round your percentages; no one cares about the .4 in a
17.4% and the extra digit makes the tables much harder to read.

You might also want to look at a few additional resources that I like
and use, which are described at

http://www.childrensmercy.org/stats/weblog2005/NumbersTablesCharts.asp
--
Steve Simon, Standard Disclaimer
Two free webinars coming soon!
"What do all these numbers mean? Odds ratios,
relative risks, and number needed to treat"
Thursday, December 17, 2009, 11am-noon, CST.
"The first three steps in a descriptive
data analysis, with examples in PASW/SPSS"
Thursday, January 21, 2010, 11am-noon, CST.
Details at www.pmean.com/webinars

[Sarah]

Thank you Steve, thats excellent help.
Thank you all for the comments, its been very useful!

On 16 Dec, 16:25, "Steve Simon, P.Mean Consulting" <n...@pmean.com>
wrote:

> http://www.pmean.com/news/2009-09.html#3http://www.childrens-mercy.org/stats/weblog2006/RoundingNumbers.asphttp://www.childrens-mercy.org/stats/model/percentage.asp