Outputs of NiMARE

NiMARE includes a wide range of tools with a correspondingly large number of possible outputs. Here we outline the rules we apply to NiMARE outputs.

File names

NiMARE-generated files, especially ones made by meta-analyses, follow a naming convention somewhat based on BIDS.

Here is the basic naming convention for statistical maps:

<value>[_desc-<label>][_level-<cluster|voxel>][_corr-<FWE|FDR>][_method-<label>].nii.gz

First, the value represents type of data in the map (e.g., z-statistic, t-statistic). Some of the values found in NiMARE include:

  • z: Z-statistic

  • t: T-statistic

  • p: p-value

  • logp: Negative base-ten logarithm of p-value

  • chi2: Chi-squared value

  • prob: Probability value

  • stat: Test value of meta-analytic algorithm (e.g., ALE values for ALE, OF values for MKDA)

  • est: Parameter estimate (IBMA only)

  • se: Standard error of the parameter estimate (IBMA only)

  • tau2: Estimated between-study variance (IBMA only)

  • sigma2: Estimated within-study variance (IBMA only)

Note

For one-sided tests, p-values > 0.5 will have negative z-statistics. These values should not be confused with significant negative results. As a result, in NiMARE, these values are replaced by 0.

Next, a series of key/value pairs describe the methods applied to generate the map.

  • desc: Description of the data type. Only used when multiple maps with the same data type are produced by the same method.

  • level: Level of multiple comparisons correction. Either cluster or voxel.

  • corr: Type of multiple comparisons correction. Either FWE (familywise error rate) or FDR (false discovery rate).

  • method: Name of the method used for multiple comparisons correction (e.g., “montecarlo” for a Monte Carlo procedure).

File contents

NiMARE outputs unthresholded statistical maps. Users may then threshold their results separately.

This may result in some confusion for cluster-level corrected maps, in which each _cluster_ (after applying a voxel-wise cluster-defining threshold) has an overall significance level. As such, cluster-level corrected maps contain zeros for all non-significant voxels after applying the cluster-defining threshold, and each cluster has a single value across all voxels in the cluster. All clusters surviving the cluster-defining threshold will be included in the map, including clusters that have very high p-values.