TY  - JOUR
T1  - EXcess significance bias in the literature on brain volume abnormalities
AU  - Ioannidis JA
Y1  - 2011/08/01
N1  - 10.1001/archgenpsychiatry.2011.28
JO  - Archives of General Psychiatry
SP  - 773
EP  - 780
VL  - 68
IS  - 8
N2  - Context 
                  Many studies report volume abnormalities in diverse brain structures in patients with various mental health conditions.Objective 
                  To evaluate whether there is evidence for an excess number of statistically significant results in studies of brain volume abnormalities that suggest the presence of bias in the literature.Data Sources 
                  PubMed (articles published from January 2006 to December 2009).Study Selection 
                  Recent meta-analyses of brain volume abnormalities in participants with various mental health conditions vs control participants with 6 or more data sets included, excluding voxel-based morphometry.Data Extraction 
                  Standardized effect sizes were extracted in each data set, and it was noted whether the results were“positive” (P < .05) or not. For each data set in each meta-analysis, I estimated the power to detect atα = .05 an effect equal to the summary effect of the respective meta-analysis. The sum of the power estimates gives the number of expected positive data sets. The expected number of positive data sets can then be compared against the observed number.Data Synthesis 
                  From 8 articles, 41 meta-analyses with 461 data sets were evaluated (median, 10 data sets per meta-analysis) pertaining to 7 conditions. Twenty-one of the 41 meta-analyses had found statistically significant associations, and 142 of 461 (31%) data sets had positive results. Even if the summary effect sizes of the meta-analyses were unbiased, the expected number of positive results would have been only 78.5 compared with the observed number of 142 (P < .001).Conclusion 
                  There are too many studies with statistically significant results in the literature on brain volume abnormalities. This pattern suggests strong biases in the literature, with selective outcome reporting and selective analyses reporting being possible explanations.
SN  - 0003-990X
M3  - doi: 10.1001/archgenpsychiatry.2011.28
UR  - http://dx.doi.org/10.1001/archgenpsychiatry.2011.28
ER  -