pymare.stats.q_gen

q_gen(y, v, X, tau2)

Calculate a generalized form of Cochran’s Q-statistic.

This version of the Q statistic is described in Veroniki et al.[1].

Parameters:

• y (numpy.ndarray) – 1d array of study-level estimates

• v (numpy.ndarray) – 1d array of study-level variances

• X (numpy.ndarray) – 1d or 2d array containing study-level predictors (including intercept); has dimensions K x P, where K is the number of studies and P is the number of predictor variables.

• tau2 (float) – Between-study variance. Must be >= 0.

Returns:

A float giving the value of Cochran’s Q-statistic.

Return type:

float

References

[1]

Areti Angeliki Veroniki, Dan Jackson, Wolfgang Viechtbauer, Ralf Bender, Jack Bowden, Guido Knapp, Oliver Kuss, Julian PT Higgins, Dean Langan, and Georgia Salanti. Methods to estimate the between-study variance and its uncertainty in meta-analysis. Research synthesis methods, 7(1):55–79, 2016. URL: https://doi.org/10.1002/jrsm.1164, doi:10.1002/jrsm.1164.