Modified Nel and Van der Merwe test for the multivariate Behrens–Fisher problem

110 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Small-Sample Adjustments for Tests of Moderators and Model Fit Using Robust Variance Estimation in Meta-Regression (2015, methodology): “Versions of this approach are found in the literature on heteroskedastic ANOVA (Zhang, 2013), MANOVA with unequal variance–covariance structures (Krishnamoorthy & Yu, 2004; Nel & van der Merwe, 1986; Zhang, 2012), and GEE models (Pan & Wall, 2002).”
A parametric bootstrap solution to the MANOVA under heteroscedasticity (2010, methodology): “For the special case of comparing two mean vectors, we developed an approximate test that is the same as the existing satisfactory test in Krishnamoorthy and Yu [18].”
Small-Sample Methods for Cluster-Robust Variance Estimation and Hypothesis Testing in Fixed Effects Models (2016, background): “Nel and van der Merwe (1986) proposed an AHT-type test for equality of multivariate means across two samples with unequal variance-covariance matrices (i.e., the multivariate Behrens–Fisher problem; see also Krishnamoorthy and Yu 2004).”
On the Behrens–Fisher problem: A globally convergent algorithm and a finite-sample study of the Wald, LR and LM tests (2008, methodology): “, Yao [37], Subrahmaniam and Subrahmaniam [33], Kim [16] and Krishnamoorthy and Yu [18]), we performed tests for the low dimensional cases of d = 2,5 and 10, but we also included the higher-dimensional cases of d = 25,50,75, 100 and 200.”