Description Usage Arguments Details Value Author(s) References Examples

This function computes the variance-covariance matrix of variance components (VC) either
applying the approach given in the *1st* reference ('method="scm"') or using
the approximation given in the *2nd* reference ('method="gb"').

1 |

`obj` |
(VCA) object |

`method` |
(character) string, optionally specifying whether to use the algorithm given in the 1st reference ("scm") or in the 2nd refernce ("gb"). If not not supplied, the option is used coming with the 'VCA' object. |

`quiet` |
(logical) TRUE = will suppress any warning, which will be issued otherwise |

When 'method="scm"' is used function `getVCvar`

is called implementing this rather
time-consuming algorithm. Both approaches, respectively the results they generate, diverge for
increasing degree of unbalancedness. For balanced designs, they seem to differ only due to
numerical reasons (error propagation).

This function is called on a 'VCA' object, which can be the sole argument. In this case the value
assigned to element 'VarVC.method' of the 'VCA' object will be used
(see `getVCvar`

for computational details).

(matrix) corresponding to variance-covariance matrix of variance components

Andre Schuetzenmeister [email protected], Florian Dufey [email protected]

Searle, S.R, Casella, G., McCulloch, C.E. (1992), Variance Components, Wiley New York

Giesbrecht, F.G. and Burns, J.C. (1985), Two-Stage Analysis Based on a Mixed Model: Large-Sample Asymptotic Theory and Small-Sample Simulation Results, Biometrics 41, p. 477-486

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VCA documentation built on July 19, 2018, 5:05 p.m.

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