nimare.meta.cbma.weights.normalize_weights

normalize_weights(raw_weights, n_studies)

Rescale relative weights so they sum to n_studies.

With uniform inputs every weight is exactly 1.0, so an unweighted analysis is untouched and the statistic stays the count of activating contrasts. Dividing the result by n_studies recovers the weighted proportion of Wager et al.[1].

References

[1]

Tor D Wager, Martin A Lindquist, Thomas E Nichols, Hedy Kober, and Jared X Van Snellenberg. Evaluating the consistency and specificity of neuroimaging data using meta-analysis. NeuroImage, 45(1 Suppl):S210–S221, 2009. URL: https://doi.org/10.1016/j.neuroimage.2008.10.061, doi:10.1016/j.neuroimage.2008.10.061.

Examples using nimare.meta.cbma.weights.normalize_weights

Sample-size weighting in MKDA

Sample-size weighting in MKDA