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.
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 and tables:
value represents type of data in the map (e.g., z-statistic, t-statistic).
Some of the values found in NiMARE include:
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)
label: Label map
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
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).
diag: Type of diagnostic. Either
Jackknife(jackknife analysis) or
tab: Type of table. Either
clust(clusters table) or
tail: Sign of the tail for label maps. Either
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.