Is there a way to consider additional parameters for a coordinate-based meta-analysis

Hi all, I am very new to NiMare (and coding in general). I have been using it to perform a coordinate-based meta-analysis, and I based my data on the example json file that is available on the NiMare website. I was wondering if you could help me with a couple of things: on top of the sample size, I also wanted to try and consider other parameters, like the statistical value of each peak, or the cluster size, and I was wondering if there’s a way to add this to the json file. I was also wondering if one of the CBMA methods would be better suited to take this into account, considering that I have 17 studies in total, the majority of which derive their coordinates from analysis that compare control and study sample, and two of them derive them from analyses of severity within the sample. In relation to this last point, my other question would be, is it ok to get these studies together in the same meta-analysis, and is it correct to use the total sample size for each study, or is that a better way to do that (e.g. adding in the json file two sample size for study and control samples in the “between” analyses?). Hope this makes sense and would really appreciate any guidance you can provide on this.

Hello Sara,

You can include that info in the JSON file, but it won’t be used by any of NiMARE’s tools at the moment.

NiMARE currently doesn’t include any CBMA algorithms that would use this kind of peak-level information. Yifan Yu and @jdkent are currently working on adding a model-based method that would, I think, incorporate at least the peaks’ statistical values, if not the associated cluster sizes.

Outside of NiMARE, the only algorithm that uses peak-level information (at least to my knowledge) is SDM. I don’t think SDM will use the cluster sizes at all, but it does use peak statistic values. The NiMARE developers have started implementing the SDM algorithm within NiMARE, but this is a long-term goal and the actual SDM software is the only tool available to actually run the current SDM algorithm.

I’m not sure. My first thought is that the two severity analyses should be excluded, but I’ll ping @angielaird in case she has a better recommendation.

You can put multiple sample sizes in the NiMARE JSON file. I believe that the mean of the sample sizes will automatically be calculated and used by any NiMARE CBMA algorithms that use that information (i.e., ALE, ALESubtraction, and SCALE).


Hi Taylor, thanks so much for answering so quickly and so thoroughly! Really appreciate all the information of point 2, I think we might still go with NiMare but I’ll have a think about that specifically with my supervisor as well. For point 3 thanks so much for double checking, I thought about that as well, of excluding those two studies, but if angielaird might have a better recommendation that would be amazing! For point 4 and potentially 1, could I be a pest and ask (I am really not that comfortable with coding, I have never done anything personally yet) is there an example of how I could add those points in the json file without messing it up? Again thanks so much, that was really helpful!

Yes, given the breakdown of contrasts (15 case/control, 2 severity correlations), I would exclude the latter.