Re: meta-analysis

[Rich Ulrich]

On 17 Jun 2001 04:34:26 -0700, [EMAIL PROTECTED] (Marc)
wrote:

 I have to summarize the results of some clinical trials.
 Unfortunately the reported information is not complete.
 The information given in the trials contain:
 
 (1) Mean effect in the treatment group (days of hospitalization)
 
 (2) Mean effect in the control group (days of hospitalization)
 
 (3) Numbers of patients in the control and treatment group
 
 (4) p-values of a t-test (between the differences of treatment
 and control)
 My question:
 How can I calculate the variance of treatment difference which I need
 to perform meta-analysis? Note that the numbers of patients in the

Aren't you going too far?  You said you have to summarize.
Well, summarize.  The difference is in terms of days.  
Or it is in terms of percentage of increase.

And you have the t-test and p-values.  

You might be right in what you propose, but I think
you are much more likely to produce a useful report 
if you keep it simple.

You are right; meta-analyses are complex.  And a 
majority of the published ones are (in my opinion) awful.
--
Rich Ulrich, [EMAIL PROTECTED]
http://www.pitt.edu/~wpilib/index.html


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Re: meta-analysis

[Donald Burrill]

On 17 Jun 2001, Marc wrote (edited):

 I have to summarize the results of some clinical trials.
 The information given in the trials contain:
 
 Mean effects (days of hospitalization) in treatment  control groups; 
 numbers of patients in the groups;  p-values of a t-test (of the 
 difference between treatment and control) .
 My question:  How can I calculate the variance of the treatment 
 difference, which I need to perform meta-analysis?  Note that the 
 numbers of patients in the groups are not equal.  
 Is it possible to do it like this:
 
 s^2 = (difference between contr and treatm)^2/ ((1/n1+1/n2)*t^2)

Yes, if you know t.  If all you know is that p  alpha for some alpha, 
you then know only that t  the t corresponding to alpha (AND you need to 
know whether the test had been one-sided or two-sided -- of course, you 
need to know that in any case), you can substitute that corresponding t 
to obtain an upper bound on s^2 -- ASSUMING that the t was calculated 
using a pooled variance (your s^2), not using the expression for separate 
variances in the denominator:  (s1^2/n1 + s2^2/n2).

Note that this s^2 is NOT the variance of the treatment difference, 
which you said you wanted to know;  it is the pooled variance estimate 
of the variance within each group.  
 The variance of the difference in treatment means, which _may_ be what 
you are interested in, would be 

(difference)^2 / t^2 

with the same caveats concerning what you know about t.

 How exact would such an approximation be?

Depends on the precision with which  p  was reported.

 
 Donald F. Burrill [EMAIL PROTECTED]
 184 Nashua Road, Bedford, NH 03110  603-471-7128



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