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Excess significance bias in the literature on brain volume abnormalities.

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TLDR
There are too many studies with statistically significant results in the literature on brain volume abnormalities that suggest strong biases in the Literature, with selective outcome reporting and selective analyses reporting being possible explanations.
Abstract
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  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  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.

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TL;DR: Significant gaps in methods reporting among fMRI studies are documented, and improved methodological descriptions in research reports would yield significant benefits for the field.
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Progressive brain changes in schizophrenia related to antipsychotic treatment? A meta-analysis of longitudinal MRI studies

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References
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Journal ArticleDOI

Amygdala volumes in mood disorders--meta-analysis of magnetic resonance volumetry studies.

TL;DR: The absence of overall differences in amygdala volumes, in the presence of significant and sometimes mirror changes in patient subgroups, demonstrates marked heterogeneity among mood disorders.
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Critical interpretation of Cochran's Q test depends on power and prior assumptions about heterogeneity

TL;DR: An evaluation of 1011 meta-analyses of clinical trials with ⩾4 studies and binary outcomes shows that power to detect typical heterogeneity was low in most situations, and usually a non-significant Q test did not change perceptibly prior convictions on heterogeneity.
Journal ArticleDOI

Disclose all data in publications.

Keith A. Baggerly
- 23 Sep 2010 - 
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Journals Should Publish All “Null” Results and Should Sparingly Publish “Positive” Results

TL;DR: The X team (real but anonymous here) meets successfully most proposed criteria and has published nine articles on mostly brand new (but also some replicated) gene-disease research.
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MR image-based measurement of rates of change in volumes of brain structures. Part II: application to a study of Alzheimer’s disease and normal aging

TL;DR: Rates of brain atrophy, especially in specific regions of the brain, based on MR images can provide sensitive measures for evaluating the progression of AD and will be useful for the evaluation of therapeutic effects of novel therapies for AD.
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