http://www.nitrc.org/forum/forum.php?forum_id=8252 <table border="0" width="100%"><tr><td align="left"/></tr></table> <p><b>The Influence of Study-Level Inference Models and Study Set Size on Coordinate-Based fMRI Meta-Analyses.</b></p> <p>Front Neurosci. 2017;11:745</p> <p>Authors: Bossier H, Seurinck R, Kühn S, Banaschewski T, Barker GJ, Bokde ALW, Martinot JL, Lemaitre H, Paus T, Millenet S, Moerkerke B</p> <p>Abstract<br/> Given the increasing amount of neuroimaging studies, there is a growing need to summarize published results. Coordinate-based meta-analyses use the locations of statistically significant local maxima with possibly the associated effect sizes to aggregate studies. In this paper, we investigate the influence of key characteristics of a coordinate-based meta-analysis on (1) the balance between false and true positives and (2) the activation reliability of the outcome from a coordinate-based meta-analysis. More particularly, we consider the influence of the chosen group level model at the study level [fixed effects, ordinary least squares (OLS), or mixed effects models], the type of coordinate-based meta-analysis [Activation Likelihood Estimation (ALE) that only uses peak locations, fixed effects, and random effects meta-analysis that take into account both peak location and height] and the amount of studies included in the analysis (from 10 to 35). To do this, we apply a resampling scheme on a large dataset (N = 1,400) to create a test condition and compare this with an independent evaluation condition. The test condition corresponds to subsampling participants into studies and combine these using meta-analyses. The evaluation condition corresponds to a high-powered group analysis. We observe the best performance when using mixed effects models in individual studies combined with a random effects meta-analysis. Moreover the performance increases with the number of studies included in the meta-analysis. When peak height is not taken into consideration, we show that the popular ALE procedure is a good alternative in terms of the balance between type I and II errors. However, it requires more studies compared to other procedures in terms of activation reliability. Finally, we discuss the differences, interpretations, and limitations of our results.<br/> </p><p>PMID: 29403344 [PubMed]</p> en-us Copyright 2000-2026 NITRC OSI Fri, 01 May 2026 0:59:55 GMT http://blogs.law.harvard.edu/tech/rss NITRC RSS generator