sandbox.stats.multicomp.varcorrection_unbalanced()

statsmodels.sandbox.stats.multicomp.varcorrection_unbalanced

statsmodels.sandbox.stats.multicomp.varcorrection_unbalanced(nobs_all, srange=False) [source]

correction factor for variance with unequal sample sizes

this is just a harmonic mean

Parameters:	nobs_all : array_like The number of observations for each sample srange : bool if true, then the correction is divided by the number of samples for the variance of the studentized range statistic
Returns:	correction : float Correction factor for variance.

Notes

variance correction factor is

1/k * sum_i 1/n_i

where k is the number of samples and summation is over i=0,...,k-1. If all n_i are the same, then the correction factor is 1.

This needs to be multiplied by the joint variance estimate, means square error, MSE. To obtain the correction factor for the standard deviation, square root needs to be taken.