Meta-analysis vs. naïve pooling [General Sta­tis­tics]

posted by Helmut Homepage – Vienna, Austria, 2010-04-09 22:33 (5911 d 07:51 ago) – Posting: # 5070
Views: 10,925

Dear D. Labes & earlybird!

SUGI 27: SAS® Tools for Meta-analysis


Is it really that easy? See the example at page 2:

Suppose we have [...] two identical studies, following the same protocol, using the same treatments, using the same response variable, and suppose once again that we can obtain the data. We could then fit a mixed model (if we wanted to treat study as a random effect), using PROC MIXED, or an ANOVA model (if we wanted to treat study as a fixed effect), using PROC GLM.


It took me while to find suitable data in my files - who repeats a study without any modifications? This was the closest I could get: AUC-data, same protocol (clinical site, sampling schedule, analytical method,...). Different batches of test and reference were used (actually the reference came from two countries).

Single studies
Fixed: sequence+treatment+period
Random: subject(sequence)
Study 1: n=12, 99.93% (94.46% - 105.71%), CVintra 7.61%
Study 2: n=13, 91.00% (85.26% -  97.12%), CVintra 9.24%


Naïve pooling (study not in the model)
Fixed: sequence+treatment+period
Random: subject(sequence)
Pooled 1: n=25, 95.05% (90.86% -  99.43%), CVintra 9.31%

Interesting: The CV is higher than in either study despite the higher sample size.

OK, let's add the study to the model...
Fixed: sequence+treatment+period
Random: subject(sequence)+study
Pooled 2: n=25, 95.05% (90.85% -  99.43%), CVintra 9.31%

Aha No.1 :confused:

And code all as fixed...
Fixed: sequence+treatment+period+subject(sequence)+study
Pooled 3: n=25, 95.05% (90.86% -  99.43%), CVintra 9.31%

Aha No.2

Besides some minor differences in the second decimal of the lower CL all models came up the same. Why all the fuzz with sequential designs, alpha-adjustements and the like - if I can simply throw all data into the big pot, stir it up, and voilá...

Again: Is it really that easy?
Both studies were already evaluated, the alpha is 'consumed' - any professional statisticians out there?

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